Browse Topic: Electrical, Electronics, and Avionics

Items (53,046)

Probabilistically Extended Ontologies a basis for systematic testing of ML-based systems

2024-01-3002To be published on 07/02/2024

Autonomous driving is a hot topic in the automotive domain, and there is an increasing need to prove its reliability. They use machine learning techniques, which are themselves stochastic techniques based on some kind of statistical inference. The occurrence of incorrect decisions is part of this approach and often not directly related to correctable errors. The quality of the systems is indicated by statistical key figures such as accuracy and precision. Numerous driving tests and simulations in simulators are extensively used to provide evidence. However, the basis of all descriptive statistics is a random selection from a probability space. The difficulty in testing or constructing the training and test data set is that this probability space is usually not well defined. To systematically address this shortcoming, ontologies have been and are being developed to capture the various concepts and properties of the operational design domain. They serve as a basis for the specification

Wiesbrock, Hans Werner, Grossmann, Jürgen

Automated Park and Charge: Concept and Energy Demand Calculation

2024-01-2988To be published on 07/02/2024

In this paper we are presenting the concept of automated park and charge functions in different use scenarios. The main scenario is automated park and charge in production and the other use scenario is within automated valet parking in parking garages. The automated park and charge in production is developed within the scope of the publicly funded project E-Self. The central aim of the project is the development and integration of automated driving at the end-of-line in the production at Ford Motor Company's manufacturing plant in Cologne. The driving function thereby is mostly based upon automated valet driving with an infrastructure based perception and action planning. Especially for electric vehicles the state of charge of the battery is critical, since energy is needed for all testing and driving operations at end-of-line. In addition long shipping times require in combination with a specific state-of-charge requirement at customer delivery a recharging within the production

Sturm, Axel Wolfgang, Kascha, Marcel, Mejri, Mohamed Amine, Henze, Roman, Heister, Laura, Mueck, Alexander

Cyber Security Approval Criteria: Application of UN R155

2024-01-2983To be published on 07/02/2024

The UN R155 regulation is the first automotive cyber security regulation and has made security a mandatory approval criterion for new vehicle types. This establishes internationally harmonized security requirements for market approval. As a result, the application of the regulation presents manufacturers and suppliers with the challenge of demonstrating compliance. At process level the implementation of a Cyber Security Management System (CSMS) is required while at product level, the Threat Assessment and Risk Analysis (TARA) forms the basis to identify relevant threats and corresponding mitigation strategies. Overall, an issued type approval is internationally recognized by the member states of the UN 1958 Agreement. International recognition implies that uniform assessment criteria are applied to demonstrate compliance and to decide whether security efforts are sufficient. However, as security engineering according to ISO/SAE 21434 follows a risk-based approach, there are currently

Hellstern, Mona, Langhanki, Stefan, Grün, Florian, Kriesten, Reiner, Sax, Eric

Enabling the security of global time in software-defined vehicles (SGTS, MACsec

2024-01-2978To be published on 07/02/2024

The global time that is propagated and synchronized in the vehicle E/E architecture is used in safety-critical, security-critical, and time-critical applications (e.g., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384. These failures reduce the vehicle availability, robustness, and safety of the road user. IEEE 1588 lists four mechanisms (integrated security mechanism, external security mechanism, architectural solution, and monitoring & management) to secure the global time. AUTOSAR defines the architecture and detailed specifications for the integrated security mechanism "Secured Global Time Synchronization (SGTS)" to secure the global time on automotive networks (CAN, FlexRay, Ethernet). However, there are also external

Kumaraswamy, Pavithra, Rus, Andrei

Electromagnetic Compatibility Assessment of Electric Vehicles During DC-Charging with European Combined Charging System

2024-01-3008To be published on 07/02/2024

The ongoing energy transition will have a profound impact on future mobility, with electrification playing a key role. Battery electric vehicles (EVs) are the dominant technology, relying on the conversion of alternating current (AC) from the grid to direct current (DC) to charge the traction battery. This process involves power electronic components such as rectifiers and DC/DC converters operating at high switching frequencies in the kHz range. Fast switching is essential to minimize losses and improve efficiency, but it might also generate electromagnetic interferences (EMI). Hence, electromagnetic compatibility (EMC) testing is essential to ensure reliable system operations and to meet international standards. During DC charging, the AC/DC conversion takes place off-board in the charging station, allowing for better cooling and larger components, resulting in increased power transfer, currently up to 350 kW. The EMC requirements for this charging method are outlined in IEC 61851-21

Supa Stölben, Inti Runa, Beltle, Michael, Tenbohlen, Stefan

Measurements in the Recirculation Path of a Fuel Cell System

2024-01-3009To be published on 07/02/2024

When using "green" hydrogen, fuel cell technology plays a key role in emission-free mobility. A powertrain based on fuel cells (FC) shows its advantages over battery-electric powertrains when the requirement profile primarily demands high performance over a longer period of time, high flexible availability and short refueling times. In addition, FC achieves higher effi-ciencies than the combustion of hydrogen in a gas engine, meaning that the chemical energy is used more efficiently than with established combustion engines. When using FC technology, numerous companies in Baden-Württemberg can contribute their specific expertise from the traditional automotive construction and supplier business. This includes auxiliary units in the air (cathode) and hydrogen (anode) path, such as the air compressor, the H2 recycling pump, humidifier, cooling system, power electronics, valve and pressure tank technology as well as components of the fuel cell stack itself. The periphery of the media paths

Allmendinger, Frank, Martin, Benedikt, Schmidtmann, Marlen

Standardized Differential Inductive Positioning System for Wireless Charging of Electric Vehicles

2024-01-2987To be published on 07/02/2024

To shape future mobility MAHLE has committed itself to foster wireless charging for electrical vehicles. The standardized wireless power transfer of 11 kW at a voltage level of 800 V significantly improves the end user experience for charging an electric vehicle without the need to handle a connector and cable anymore. Combined with automated parking and autonomous driving systems, the challenge to charge fleets without user interaction is solved. Wireless charging is based on inductive power transfer. In the ground assembly’s (GA) power transfer coil, a magnetic field is generated which induces a voltage in the vehicle assembly (VA) power transfer coil. To transfer the power from grid to battery with a high efficiency up to 92% the power transfer coils are compensated with resonant circuits. In this paper the Differential-Inductive-Positioning-System (DIPS) to align a vehicle on the GA for parking will be presented. This system utilizes five standardized magnetic fields which are

Boettigheimer, Mike, Grabherr, Philip

Charging infrastructure for employer parking – Real data analysis and charging algorithms for future customer demands

2024-01-2980To be published on 07/02/2024

The mobility industry and the entire ecosystem is currently striving towards sus-tainable mobility which leads to continuous production ramp-up of electrified vehicles. The parallel increase of the charging infrastructure is faced with various challenges regarding needed investments and the connection into the electricity grid. MAHLE chargeBIG offers centralized and large scaled charging infrastruc-ture with more than 1,800 already installed charging points. This presentation and paper is evaluating the functionality of the system by ana-lyzing backend real data of various employer parking installations. It can be shown and proven that a single-phase charging concept is sufficient and able to manage most customer relevant charging events by considering the needs and limitations of the related electricity grid infrastructure. Smart charging algorithms enable the integration of the charging infrastructure in smart grid company environments

Mehlig, Dennis, Krumbholz, Matthias, Gerstadt, Max

Next-gen battery strategies 2027+: Potentials and challenges for future battery designs and diversification in product portfolios to serve a large bandwidth of market applications

2024-01-3018To be published on 07/02/2024

The pace of innovations in battery development is revolutionizing the landscape and opportunities for energy storage applications leading to a stronger market segmentation enabling a better suitability to fulfill specific application requirements. For automotive applications, several approaches to increase energy densities, to improve fast charging performance, and to reduce cost on a pack level are considered. Among them, a promising example is the direct integration of battery cells into the battery pack (Cell-to-pack; CTP) or vehicle (Cell-to-chassis, CTC) to increase energy densities and to reduce costs, as already commercialized by Tesla, CATL and others. In the pack development, especially Asian players are one of the frontrunners, where e.g., hybrid cell battery systems with a mixture of cells with different cathode chemistries as introduced by NIO, are experiencing a high interest of the market. Furthermore, the implementation of battery swapping concepts is gaining stronger

Miller, Ines

FMCW Lidar Simulation with Ray Tracing and Standardized Interfaces

2024-01-2977To be published on 07/02/2024

In pursuit of safety validation of automated driving functions, efforts are being made to accompany real world test drives by test drives in virtual environments. To be able to transfer highly automated driving functions into a simulation, models of the vehicle’s perception sensors such as lidar, radar and camera are required. In addition to the classic pulsed time-of-flight (ToF) lidars, the growing availability of commercial frequency modulated continuous wave (FMCW) lidars sparks interest in the field of environment perception. This is due to advanced capabilities such as directly measuring the target’s relative radial velocity based on the Doppler effect. In this work, an FMCW lidar sensor simulation model is introduced, which is divided into the components of signal propagation and signal processing. The signal propagation is modeled by a ray tracing approach simulating the interaction of light waves with the environment. For this purpose, an ASAM Open Simulation Interface (OSI

Hofrichter, Kristof, Linnhoff, Clemens, Elster, Lukas, Peters, Steven

Enhancing BEV Energy Management: Neural Network-Based System Identification for Thermal Control Strategies

2024-01-3005To be published on 07/02/2024

Modeling thermal systems in Battery Electric Vehicles (BEVs) is crucial for enhancing energy efficiency through predictive control strategies, thereby extending vehicle range. A major obstacle in this modeling is the often limited availability of detailed system information. This research introduces a methodology using neural networks for system identification, a powerful technique capable of approximating the physical behavior of thermal systems with minimal data requirements. By employing black-box models, this approach supports the creation of optimization-based operational strategies, such as Model Predictive Control (MPC) and Reinforcement Learning-based Control (RL). The system identification process is executed using MATLAB Simulink, with virtual training data produced by validated Simulink models to establish the method's feasibility. The neural networks utilized for system identification are implemented in MATLAB code. This study conducts a comparative analysis between

Franke, Kai, Hemkemeyer, David, Schutzeich, Patrick, Schäfers, Lukas, Pischinger, Stefan

Thermal Management System for Battery Electric Heavy-Duty Trucks

2024-01-2971To be published on 07/02/2024

On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range. The main function is to protect the

Gajowski, Daniel, Wenzel, Wolfgang, Hütter, Matthias

Designing a Prototype of a Mobile Charging Robot for Charging of Electric Vehicles

2024-01-2990To be published on 07/02/2024

As the market for electric vehicles grows, so does the demand for appropriate charging infrastructure. The availability of sufficient charging points is essential to increase public acceptance of electric vehicles and to avoid the so-called “charging anxiety”. However, the charging stations currently installed may not be able to meet the full charging demand, especially in areas where there is a general lack of grid infrastructure, or where the fluctuating nature of charging demand requires flexible, high-power charging solutions that do not require expensive grid extensions. In such cases, the use of mobile charging stations provides a good opportunity to complement the existing charging network. This paper presents a prototype of a mobile charging solution that is being developed as part of an ongoing research project, and discusses different use cases. The solution presented consists of a semi-autonomous robotic platform equipped with a high voltage battery and multiple charging

Wessel, Patricia, Faßbender, Max, Gerz, Jonathan, Andert, Jakob

Environment-Adaptive Localization based on GNSS, Odometry and LiDAR Systems

2024-01-2986To be published on 07/02/2024

In the evolving landscape of automated driving systems, the critical role of vehicle localization within the autonomous driving stack is increasingly evident. Traditional reliance on Global Navigation Satellite Systems (GNSS) proves to be inadequate, especially in urban areas where signal obstruction and multipath effects degrade accuracy. Addressing this challenge, this paper details the enhancement of a localization system for autonomous public transport vehicles, focusing on mitigating GNSS errors through the integration of a LiDAR sensor. The approach involves creating a 3D map using the factor graph-based LIO-SAM algorithm based on GNSS, vehicle odometry, IMU and LiDAR data. The algorithm is adapted to the use-case by adding a velocity factor and altitude data from a Digital Terrain model. Based on the map a state estimator is proposed, which combines high-frequency LiDAR odometry based on FAST-LIO with low-frequency absolute multiscale ICP-based LiDAR position estimation. The

Kramer, Markus, Beierlein, Georg

Simulating Cloud Environments of Connected Vehicles for Anomaly Detection

2024-01-2996To be published on 07/02/2024

The emergence of connected vehicles is driven by increasing customer and regulatory demands. To meet these, more complex software applications, some of which require service-based cloud and edge backends, are developed. Due to the short lifespan of software, it becomes necessary to keep these cloud environments and their applications up to date with security updates and new features. However, as new behavior is introduced to the system, the high complexity and interdependencies between components can lead to unforeseen side effects in other system parts. As such, it becomes more challenging to recognize whether deviations to the intended system behavior are occurring, ultimately resulting in higher monitoring efforts and slower responses to errors. To overcome this problem, a simulation of the cloud environment running in parallel to the system is proposed. This approach enables the live comparison between simulated and real cloud behavior. Therefore, a concept is developed mirroring

Weiß, Matthias, Stümpfle, Johannes, Dettinger, Falk, Jazdi, Nasser, Weyrich, Michael

What is going on around the Automotive PowerNet - An overview of state-of-the-art PowerNet, insights into the new trends, and a simulation solution to keep pace with architectural changes

2024-01-2985To be published on 07/02/2024

The automotive PowerNet is facing a major transformation. The three main drivers are: • Increasing power • Availability requirements • PowerNet complexity and cost reduction These driving factors result in a wide variety of possible future PowerNet topologies. The increasing power demand is among others caused by the progressive electrification of formerly mechanical components and the trend of increasing number of comfort loads. This leads to a steady increase in installed electrical power. X-by-wire systems and autonomous driving functions result in higher availability requirements. As a result, the power supply of all safety-critical loads must always be kept sufficiently stable. To reduce costs and increase reliability, the car manufacturers aim to reduce the complexity of the PowerNet System, including the wiring harness and the controller network. The wiring harness e.g., is currently one of the costliest parts of modern cars. These challenges are met with different concepts. To

Jagfeld, Sebastian Michael Peter, Weldle, Richard, Knorr, Rainer, Fill, Alexander, Birke, Kai Peter

Graph based cooperation strategies for automated vehicles in mixed traffic

2024-01-2982To be published on 07/02/2024

In the context of urban smart mobility, vehicles have to communicate with each other, surrounding infrastructure, and other traffic participants. By using Vehicle2X communication, it is possible to exchange the vehicles’ position, driving dynamics data, or driving intention. This concept yields the use for cooperative driving in urban environments. Based on current V2X-communication standards, a methodology for cooperative driving of automated vehicles in mixed traffic scenarios is presented. Initially, all communication participants communicate their dynamic data and planned trajectory, based on which a prioritization is calculated. Therefore, a decentralized cooperation algorithm is introduced. The approach is that every traffic scenario is translatable to a directed graph, based in which a solution for the cooperation problem is computed via an optimization algorithm. This solution is either computed decentralized by various traffic participants, who share and compare their

Flormann, Maximilian, Henze, Roman

Design of an Alternative Hardware Abstraction Layer for Embedded Systems with Time-Controlled Hardware Access

2024-01-2989To be published on 07/02/2024

This paper proposes a novel approach to the design of a Hardware Abstraction Layer (HAL) specifically tailored to embedded systems, placing a significant emphasis on time-controlled hardware access. The general concept and utilization of a HAL in industrial projects are widespread, serving as a well-established method in embedded systems development. HALs enhance application software portability, simplify underlying hardware usage by abstracting its inherent complexity and reduce overall development costs through software reusability. Beyond these established advantages, this paper introduces a conceptual framework that addresses critical challenges related to debugging and mitigates input-related problems often encountered in embedded systems. This becomes particularly pertinent in the automotive context, where the intricate operational environment of embedded systems demands robust solutions. The HAL design presented in this paper mitigates these issues. The design is structured as a

Simmann, Gabriel, Veeranna, Vinay, Kriesten, Reiner

Runtime Safety Assurance of Autonomous Last-Mile Delivery Vehicles in Urban-like Environment

2024-01-2991To be published on 07/02/2024

The conventional process of last-mile delivery logistics often leads to safety problems for road users and a high level of environmental pollution. Delivery drivers must deal with frequent stops, search for a convenient parking spot and sometimes navigate through the narrow streets causing traffic congestion and possibly safety issues for the ego vehicle as well as for other traffic participants. This process is not only time consuming but also environmentally impactful, especially in low-emission zones where prolonged vehicle idling can lead to air pollution and to high operational costs. To overcome these challenges, a reliable system is required that not only ensures the flexible, safe and smooth delivery of goods but also cuts the costs and meets the delivery target. In the dynamic landscape of last-mile delivery, LogiSmile, an EU project, introduced a solution to urban delivery challenges through an innovative cooperation between an Autonomous Hub Vehicle (AHV) and an Autonomous

Aslam, Iqra, Aniculaesei, Adina, Buragohain, Abhishek, Zhang, Meng, Bamal, Daniel, Rausch, Andreas

Towards Future Vehicle Diagnostics in Software-Defined Vehicles

2024-01-2981To be published on 07/02/2024

Software will lead the development and life cycle of vehicles in the future. Nowadays, more and more software is being integrated into a vehicle, evolving it into a Software-Defined Vehicle (SDV). Automotive High Performance Computers (HPCs) serve as enablers by providing more computing infrastructure which can be flexibly used inside a vehicle. However, this leads to a complex vehicle system that needs to function today and in the future. Detecting and rectifying failures as quickly as possible is essential, but existing diagnostic approaches based on Diagnostic Trouble Codes (DTCs) are not designed for such complex systems and lack of flexibility. DTCs are predefined during vehicle development and changes to vehicle diagnostics require a large amount of modification work. Moreover, diagnostics are not intended to handle dynamically changing software systems and have shortcomings when applied to in-vehicle software systems. In the Cloud, there are already established approaches to

Bickelhaupt, Sandra, Hahn, Michael, Morozov, Andrey, Weyrich, Michael

Automated AI-based Annotation Framework for 3D Object Detection from LIDAR Data in Industrial Areas

2024-01-2999To be published on 07/02/2024

Autonomous Driving is being utilized in various settings, including indoor areas such as industrial halls. Additionally, LIDAR sensors are currently popular due to their superior spatial resolution and accuracy compared to RADAR, as well as their robustness to varying lighting conditions compared to cameras. They enable precise and real-time perception of the surrounding environment. Several datasets for on-road scenarios such as KITTI or Waymo are publicly available. However, there is a notable lack of open-source datasets specifically designed for industrial hall scenarios, particularly for 3D LIDAR data. Furthermore, for industrial areas where vehicle platforms with omnidirectional drive are often used, 360° FOV LIDAR sensors are necessary to monitor all critical objects. Although high-resolution sensors would be optimal, mechanical LIDAR sensors with 360° FOV exhibit a significant price increase with increasing resolution. Most existing AI models for 3D object detection in point

Abdelhalim, Gina, Simon, Kevin, Bensch, Robert, Parimi, Sai, Qureshi, Bilal Ahmed

Neural Network Modeling of Black Box Controls for Internal Combustion Engine Calibration

2024-01-2995To be published on 07/02/2024

The calibration of Engine Control Units (ECUs) for road vehicles is challenged by stringent legal and environmental regulations, coupled with short development cycles. The growing number of vehicle variants, although sharing similar engines and control algorithms, requires different calibrations. Additionally, modern engines feature increasingly number of adjustment variables, along with complex parallel and nested conditions within the software, demanding a significant amount of measurement data during development. The current state-of-the-art (White Box) model-based ECU calibration proves effective but involves considerable effort for model construction and validation. This is often hindered by limited function documentation, available measurements, and hardware representation capabilities. This article introduces a model-based calibration approach using Neural Networks (Black Box) for two distinct ECU functional structures with minimal software documentation. The ECU is operated on

Meli, Matteo, Wang, Zezhou, Bailly, Peter, Pischinger, Stefan

Enhancing Urban AEB Systems: Simulation-Based Analysis of Error Tolerance in Distance Estimation and Road-Tire Friction Coefficients

2024-01-2992To be published on 07/02/2024

Autonomous Emergency Braking (AEB) systems are critical in preventing collisions, yet their effectiveness hinges on accurately estimating the distance between the vehicle and other road users, as well as understanding road conditions. Errors in distance estimation can result in premature or delayed braking and varying road conditions alter road-tire friction coefficients, affecting braking distances. Advancements in sensor technology and deep learning have improved vehicle perception and real-world understanding. The integration of advanced sensors like LiDARs has significantly enhanced distance estimation. Cameras and deep neural networks are also employed to estimate the road conditions. However, AEB systems face notable challenges in urban environments, influenced by complex scenarios and adverse weather conditions such as rain and fog. Therefore, investigating the error tolerance of these estimations is essential for the performance of AEB systems. Determining the actual distances

Wang, Yifan, Iatropoulos, Jannes, Thal, Silvia, Henze, Roman

On-Center Steering Model for Realistic Steering Feel based on Real Measurement Data

2024-01-2994To be published on 07/02/2024

Driving simulators allow the testing of driving functions, vehicle models and acceptance assessment at an early stage. For a real driving experience, it's necessary that all immersions are depicted as realistically as possible. When driving manually, the perceived haptic steering wheel torque plays a key role in conveying a realistic steering feel. To ensure this, complex multi-body systems are used with numerous of parameters that are difficult to identify. Therefore, this study shows a method how to generate a realistic steering feel with a nonlinear open-loop model which only contains significant parameters, particularly the friction of the steering gear. This is suitable for the steering feel in the most driving on-center area. Measurements from test benches and real test drives with an Electric Power Steering (EPS) were used for the Identification and Validation of the model. The open-loop architecture on steering rack level shows adequate results and generate a nearly delay-free

Dieing, Andreas, Reuss, Hans-Christian, Schlüter, Marco

Set-up of an in-car system for investigating driving style on the basis of the 3D-method

2024-01-3001To be published on 07/02/2024

Investigating human driver behavior enhances the acceptance of the autonomous driving and increases road safety in heterogeneous environments with human-operated and autonomous vehicles. The previously established driver fingerprint model, focuses on the classification of driving style based on CAN bus signals. However, driving styles are inherently complex and influenced by multiple factors, including changing driving environments and driver states. To comprehensively create a driver profile, an in-car measurement system based on the Driver-Driven vehicle-Driving environment (3D) framework is developed. The measurement system records emotional and physiological signals from the driver, including ECG signal and heart rate. A Raspberry Pi camera is utilized on the dashboard to capture the driver's facial expressions and a trained convolutional neural network (CNN) recognizes emotion. To conduct unobtrusive ECG measurements, an ECG sensor is integrated into the steering wheel

Ji, Dejie, Flormann, Maximilian, Warnecke, Joana M., Henze, Roman, Deserno, Thomas M.

Optimization-Based Battery Thermal Management for Improved Regenerative Braking in CEP Vehicles

2024-01-2974To be published on 07/02/2024

The courier express parcel service industry (CEP industry) has experienced significant changes in the recent years due to increasing parcel volume. At the same time, the electrification of the vehicle fleets poses additional challenges. A major advantage of battery electric CEP vehicles compared to internal combustion engine vehicles is the ability to regenerate the kinetic energy of the vehicle in the frequent deceleration phases during parcel delivery. If the battery is cold the maximum recuperation power of the powertrain is limited by a reduced chemical reaction rate inside the battery. In general, the maximum charging power of the battery depends on the state of charge and the battery temperature. Due to the low power demand for driving during CEP operation, the battery self-heating is comparably low under cold ambient conditions. Without active conditioning of the battery, potential regenerative energy is lost as a result of the cold battery. This paper proposes an optimization

Rehm, Dominik, Krost, Jonathan, Meywerk, Martin, Czarnetzki, Walter

Approach for an Assistance System for E-Bikes to Implement Rider-Adaptive Support

2024-01-2979To be published on 07/02/2024

When riding an e-bike, riders are faced with the question of whether there is enough energy left in the battery to reach the destination with the desired level of support. E-bike users therefore have an existential range anxiety. Specifically, this describes the fear that the battery charge will be exhausted before there is an opportunity to recharge it and that it will no longer be possible to use the electric support. However, e-bike riders have so far had to decide for themselves whether the available battery charge is sufficient for riding the planned route or whether the desired destination can be reached. In this context, the challenge is to decide how much support can be used so that an appropriate amount of effort can be achieved for the entire journey. In order to assist e-bike riders with this problem, the objective of this paper is to present an approach towards an assistance system that provides rider-adaptive support over the entire journey of a defined route. This

Rauch, Yannick, Kriesten, Reiner

Software-supported Processes for Aerodynamic Homologation of Vehicles

2024-01-3004To be published on 07/02/2024

Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined. Absolute and

Jacob, Jan D.

A Study on RANC Technique for Server-based Control Filter Optimization

2024-01-2960To be published on 06/12/2024

Broadband active noise control algorithms require high-performance so multi-channel control to ensure high performance, which results in very high computational power and expensive DSP. When the control filter update part need a huge computational power of the algorithm is separated and calculated by the server, it is possible to reduce cost by using a low-cost DSP in a local vehicle, and a performance improvement algorithm requiring a high computational power can be applied to the server. In order to achieve the above goal, this study analyzed the maximum delay time when communication speed is low and studied response measures to ensure data integrity at the receiving location considering situations where communication speed delay and data errors occur. Accelerometer and microphone sensor signals are transmitted from the local controller to the server using a commercial wireless communication service, and the server receives them and inputs them into an algorithm to create a control

Oh, ChiSung, Ih, Kang-Duck, Kim, Hyounsuk

Adaptive Inverse Control of Vibration Exciter for Tracking Target Acceleration of a Car Subsystem

2024-01-2920To be published on 06/12/2024

This research aims to develop an inverse control method capable of adaptively simulating dynamic models of car subsystems in the rig-test condition. Accurate simulation of the actual vibration conditions is one of the most crucial factors in realizing reliable rig-test platforms. However, most typical rig tests are conducted under simple random or harmonic sweep conditions. Moreover, the conventional test methods are hard to directly adapt to the actual vibration conditions when switching the dynamic characteristics of the subsystem in the rig test. In the present work, we developed an inverse controller to adaptively control the vibration exciter referring to the target vibration signal. An adaptive LMS filter, employed for the control algorithm, updated the filter weights in real time by referring to the target and the measured acceleration signals. We utilized a car subsystem, comprising a vehicle suspension and a rigid fixture, to confirm the performance of the developed controller

Jung, GyuYeol, Lee, Sang Kwon, An, Kanghyun, Jang, Sunyoung, Shin, Taejin, Kwak, Wooseong, Kim, Howuk

AI-Based Optimization Method of Motor Design Parameters for Enhanced NVH Performance in Electric Vehicles

2024-01-2927To be published on 06/12/2024

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs. By applying AI, we developed a CatBoost-based regression model to estimate motor performance, including NVH and torque based on motor design parameters, achieving an impressive

Noh, Kyoungjin, Lee, Dongchul, Jung, Insoo, Tate, Simon, Mullineux, James, Mohd Azmin, Farraen

Sound Quality Evaluation on Noise Caused by Electric Power Steering Wheel Utilizing CNN based on Sound Metrics

2024-01-2963To be published on 06/12/2024

This research aims presents the method classifying the noise source and evaluating the sound quality of the noise caused by operating of electric power steering wheel in an electric vehicle. The steering wheel has been operated by the motor drive by electric power and it called motor-driven electric power (MDPS) system. If the motor is attached to the steering column of the steering device, it is called C-MDPS system. The steering device of the C-MDPS system comprises of motor, bearings, steering column, steering wheel and worm shaft. Among these components the motor and bearings are main noise sources of C-MDPS system. When the steering wheel is operated in an electric vehicle, the operating noise of the steering device inside the vehicle is more annoying than that in a gasoline engine vehicle since the operating noise is not masked by engine noise. Defects in the C-MDPS system worsen the operating noise of the steering system. In the paper, the method classifying defect source of the

Lee, Sang Kwon, An, Kanghyun, Kim, Seong Yeol, Kim, Doyeon, Park, Jongho, Cho, Inje, Park, Kyunghwan

Transmission of sound under the influence of various environmental conditions

2024-01-2933To be published on 06/12/2024

Electrified vehicles are particularly quiet, especially at low speeds due to the absence of combustion noises. This is why there are laws worldwide for artificial driving sounds to warn pedestrians. These sounds are generated using a so-called Acoustic Vehicle Alerting System (AVAS) which must maintain certain minimum sound pressure levels in specific frequency ranges at low speeds. The creation of the sound currently involves an iterative and sometimes time-consuming process that combines composing the sound on a computer with measuring the levels with a car on an outside noise test track. This continues until both the legal requirements and the subjective demands of vehicle manufacturers are met. To optimize this process and reduce the measurement effort on the outside noise test track, the goal is to replace the measurement with a simulation for a significant portion of the development. Since the measurement for meeting legal requirements takes place outdoors , they are subject to

Schönfeld, Nils, Gsell, Stephan, Müller, Gerhard

New Equivalent Static Load (ESL) Creation Procedure for Complete Vehicle

2024-01-2944To be published on 06/12/2024

By analyzing the dynamic distortion in all body closure openings in a complete vehicle, a better understanding of the body characteristics can be achieved compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures. The body response is measured with the so-called Multi Stethoscope (MSS) when driving a vehicle on a rough pavé road (cobble stone). The MSS is measuring the distortion in each opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality. By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified. The DDP means that

Weber, Jens, Luiz Felipe, Faria Ricardo, Bäcklund, Jesper, Vignati, Michele, Cheli, Federico

Synergizing Efficiency and Silence: A Novel Approach to E-Machine Development

2024-01-2914To be published on 06/12/2024

Traditionally, Electric Machine design has primarily focused on factors like efficiency, packaging, and cost, often neglecting the critical aspects of Noise, Vibration, and Harshness (NVH) in the early decision-making stages. This disconnect between E-Machine design teams and NVH teams has consistently posed a challenge. This paper introduces an innovative workflow that unifies these previously separate domains, facilitating comprehensive optimization by seamlessly integrating NVH considerations with other E-Machine objectives, such as electromagnetic compatibility (EMC). This paper highlights AVL's approach in achieving this transformation and demonstrates how this integrated approach sets a new standard for E-Machine design. The presented approach relies on AI-driven algorithms and computational tools. This advanced methodology harnesses the power of AI for predictive modeling and advanced optimization, resulting in the development of the optimal E-Machine for NVH without

Mehrgou, Mehdi, Garcia de Madinabeitia, Inigo, Ahmed, Mohamed Essam

Making modal analysis easy and more reliable – Reference points identification by experimental prestudy

2024-01-2931To be published on 06/12/2024

Though modal analysis is a common tool to evaluate the dynamic properties of a structure, there are still many individual decisions to be made during the process which are often based on experience and make it difficult for occasional users to gain reliable and correct results. One of those experience-based choices is the correct number and placement of reference points. This decision is especially important, because it must be made right in the beginning of the process and a wrong choice is only noticeable in the very end of the process. Picking the wrong reference points could result in incomplete modal analysis outcomes, as it might make certain modes undetectable, compounded by the user's lack of awareness about these missing modes. In the paper an innovative approach will be presented to choose the minimal number of mandatory reference points and their placement. While other approaches use results of numerical simulations or rely on a visual evaluation of measurement data by the

Kamper, Tim, Beljan, Denis, Brücher, Haiko, Wegerhoff, Matthias

The use of machine learning algorithms in the simulation of multi-layer acoustic palliatives

2024-01-2928To be published on 06/12/2024

Acoustic palliatives used in the automotive industry have evolved from simple felt and heavy layer combinations into highly complex formulations and combinations to account for higher performance targets, lower weight and inevitably cost constraints. Achieving Customer performance compliance usually involves a time-consuming exercise of material characterisation and measurement. Ideally this should be carried out via simulation, but as material mixtures and compositions become more complex, the ability to accurately simulate their acoustic performance is becoming increasingly difficult. Historically, Biot parameters and their associated TMM models have been used to simulate the acoustic performance of multi-layer material compositions. However, these simulations are not able to account for real-world complexities such as manufacturing imperfections or inter-layer gluing effects. The assumptions made by simulation models, such as a perfectly diffuse field, are rarely true in actual

Harry, Evan, Morris-Kirby, Rod, Caponio, Eleonora, Hoang, Minh Tan

Fuel Cell Fault Simulation and Detection for On Board Diagnostics using Real-Time Digital Twins

2024-37-0014To be published on 06/12/2024

The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly validated and calibrated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Software-in-the-loop (SiL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and preciously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails. Thus, it is imminent to build simulation models which can reliably reproduce failures of components like the compressor, recirculation pump, humidifier or cooling systems

Pandit, Harshad Rajendra, Dimitrakopoulos, Pantelis, Shenoy, Manish, Altenhofen, Christian

Aerodynamics' Influence on Performance in Human-Powered Vehicles for Sustainable Transportation

2024-37-0028To be published on 06/12/2024

The issue of greenhouse gas (GHG) emissions from the transportation sector is widely acknowledged. Recent years have witnessed a push towards the electrification of cars, with many considering it the optimal solution to address this problem. However, the substantial battery packs utilized in electric vehicles contribute to a considerable embedded ecological footprint. Research has highlighted that, depending on the vehicle's size, tens or even hundreds of thousands of kilometers are required to offset this environmental burden. Human-powered vehicles (HPVs), thanks to their smaller size, are inherently much cleaner means of transportation, yet their limited speed impedes widespread adoption for mid-range and long-range trips, favoring cars, especially in rural areas. This paper addresses the challenge of HPV speed, limited by their low input power and non-optimal distribution of the resistive forces. The article explores dissipation sources from rolling resistance, aerodynamics, ground

Di Gesù, Alessandro, Gastaldi, Chiara, Delprete, Cristiana

Development of a Soft-Actor Critic Reinforcement Learning Algorithm for the Energy Management of a Hybrid Electric Vehicle

2024-37-0011To be published on 06/12/2024

In recent years, the urgent need to fully exploit the fuel economy potential of the Electrified Vehicles (xEVs) through the optimal design of their Energy Management System (EMS) have led to an increasing interest in Machine Learning (ML) techniques. Among them, Reinforcement Learning (RL) seems to be one of the most promising approaches thanks to its peculiar structure, in which an agent is able to learn the optimal control strategy through the feedback received by a direct interaction with the environment. Therefore, in this study, a new Soft Actor-Critic agent (SAC), which exploits a stochastic policy, was implemented on a digital twin of a state-of-the-art diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. The SAC agent was trained to enhance the fuel economy of the PHEV while guaranteeing its battery charge sustainability. The potential of the proposed control strategy was firstly assessed on the Worldwide harmonized Light-duty vehicles Test Cycle

Rolando, Luciano, Campanelli, Nicola, Tresca, Luigi, Pulvirenti, Luca, Millo, Federico

Comparing the NVH behaviour of an innovative steel-wood hybrid battery housing design to an all aluminium design

2024-01-2949To be published on 06/12/2024

The production of electric vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. In comparison to conventional materials such as aluminum, ply wood structures exhibit beneficial damping properties. The loss factor of plywood structures with a thickness below 20 mm ranges from 0.013 to 0.032. Comparable aluminum structures however exhibit only a fraction of this loss factor with a range between 0.002 and 0.005. In this study, the potential of lightweight wood composites, specifically steel-wood hybrid structures, is investigated in the design

Wagner, Markus, Baumann, Georg, Lindbichler, Lukas, Klanner, Michael, Feist, Florian

Comparison of Performance and Efficiency of different Refrigerants at high load Conditions and their Impact on CO2eq Emissions

2024-37-0029To be published on 06/12/2024

For battery-electric vehicles (BEVs), the climate control and the driving range are crucial criteria in the ongoing electrification of automobiles in Europe towards the targeted carbon neutrality of the automotive industry. The thermal management system makes an important contribution to the energy efficiency and the cabin comfort of the vehicle. In addition to the system architecture, the refrigerant is crucial to achieve high cooling and heating performance while maintaining high efficiency and thus low energy consumption. Due to the high efficiency requirements for the vehicle, future system architectures will largely be heat pump systems. The alternative refrigerant R-474A based on the molecule R-1132(E) achieved top performance for both parameters in various system and vehicle tests. An own-built energy efficiency tool was used to determine the possible energy reduction of R-474A in comparison to refrigerant alternatives that can be translated in a CO2 reduction of the thermal

Macrì, Christian, De León, Álvaro, Flohr, Felix

Gaussian Process Surrogate Models for Vibroacoustic Simulations

2024-01-2930To be published on 06/12/2024

In vehicle NVH development, vibroacoustic simulations with Finite Element (FE) models are a common technique. The computational costs for these calculations are steadily rising due to more detailed modelling and higher frequency ranges. At the same time, the need for multiple evaluations of the same model with different input parameters, e.g., for uncertainty quantification, optimization, or robustness investigations, is also increasing. Therefore, it is crucial to reduce the computational costs in these cases. A common technique is to use surrogate models that replace the computationally intensive FE model to perform repeated evaluations. Several different methods in this area are well established, but with the continuous advancements in the field of machine learning, interesting new methods like the Gaussian Process (GP) regression arises as a promising approach. In Gaussian process regression, the model response is expressed as a stochastic process with a user-defined kernel

Luegmair, Marinus, Dantas, Rafaella, Schneider, Felix, Müller, Gerhard

Design of a Decentralized Control Strategy for CACC Systems accounting for Uncertainties

2024-37-0010To be published on 06/12/2024

Traditional CACC systems utilize inter-vehicle wireless communication to maintain minimal yet safe inter-vehicle distances, thereby improving traffic efficiency. However, introducing communication delays generates system uncertainties that jeopardize string stability, a crucial requirement for robust CACC performance. To address these issues, we introduce a decentralized Model Predictive Control (MPC) approach that incorporates Kalman Filters and state predictors to counteract the uncertainties posed by noise and communication delays. We validate our approach through MATLAB Simulink simulations, using stochastic and mathematical models to capture vehicular dynamics, Wi-Fi communication errors, and sensor noises. In addition, we explore the application of a Reinforcement Learning (RL)-based algorithm to compare its merits and limitations against our decentralized MPC controller, considering factors like feasibility and reliability

Seifoddini, Arash, Azad, Arefeh, Musa, Alessia, Misul, Daniela

Trim-structure interface modelling and simulation approaches for FEM applications

2024-01-2954To be published on 06/12/2024

Trim materials are often used for vibroacoustic energy absorption purposes within vehicles. To estimate the sound impact at a driver’s ear, the substructuring approach can be applied. Thus, transfer functions are calculated starting from the acoustic source to the car body, from the car body to the trim and, finally, from the trim to the inner cavity where the driver is located. One of the most challenging parts is the calculation of the transfer functions from the car body inner surface to the bottom trim surface. Commonly, freely laying mass-spring systems (trims) are simulated with a fixed boundary and interface phenomena such as friction, stick-slip or discontinuities are not taken into consideration. Such an approach allows for faster simulations but results in simulations strongly overestimating the energy transfer, particularly in the frequency range where the mass-spring system’s resonances take place. In the current work, several methods to model and simulate the above

Bronzova, Mariia, Bocquillet, Arnaud, Schanz, Martin

Development of an Evaluation Methodology for PIV Measurements of Low-Frequency Flow Phenomena on the Vehicle Underbody

2024-01-2939To be published on 06/12/2024

Aeroacoustics is important in the automotive industry, as it significantly influences driving comfort. Particularly in the case of battery electric vehicles (BEVs), the flow noise is already crucial at lower driving speeds, since these generate barely any drive noise and the masking effects produced by the engine are eliminated. Due to the increasing importance of drag minimization and elimination of the exhaust system, the underbody of BEVs is typically very streamlined and exhibits a low acoustic interference potential. However, even small geometric modifications to the vehicle can lead to changes in the flow around the vehicle and consequently to significant noise sources. Thus, significant flow resonances in the low frequency range below 30 Hz have been detected on certain vehicle configurations. Initial investigations have shown that the flow around the front wheel spoilers is relevant for the development of the flow phenomenon. Nevertheless, the exact and complex mechanism of

Breitenbücher, Laura, Wagner, Andreas, Wiegand, Thomas, Brink, Maarten, Buderer, Bastian

Acoustic quality assurance during End of Line engine test approval

2024-01-2922To be published on 06/12/2024

Liebherr Machines Bulle SA designs and produces High-quality diesel engines, injection systems as well as hydraulic components. Liebherr has an Acoustic End of Line (A-EoL) system on serial test benches. All engines are measured, and noises are evaluated by operators. This subjective evaluation leads to dispersion on the evaluations, particularly for whining noise. To achieve Swiss quality requirements and ensure customer satisfaction, Liebherr wishes to define a new methodology to find a quantitative and objective criterion to set a robust engine noise compliance standard. This new methodology is based on near field microphone measurement of an engine run-down. First, whining noise signatures are extracted from the raw signal. Secondly, psychoacoustic indicators are calculated on the isolated signatures. Thresholds are then established to validate engine deliveries. Finally, this process combining advanced signal processing and psychoacoustics is automated using the Ansys Sound Python

Akrout, Samir, Denisse, Robin, Dendievel, Clement, Fineschi, Fabio

Artificial Neural Network for Airborne Noise Prediction of a Diesel Engine

2024-01-2929To be published on 06/12/2024

The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points). In particular, the investigation addressed the estimation of direct Combustion Noise (CN), Sound

Credo, Giuseppe, Taddeo, Vincent, Aglietti, Filippo

A methodology to develop and validate a 75-kWh battery pack model with its cooling system under a real driving cycle

2024-37-0012To be published on 06/12/2024

A major issue of battery electric vehicles (BEV) is optimizing driving range and energy consumption. Under actual driving, transient thermal and electrical performance changes could deteriorate the battery cells and pack. These performances can be investigated and controlled efficiently with a thermal management system (TMS) via model-based development. A complete battery pack contains multiple cells, bricks, and modules with numerous coolant pipes and flow channels. However, such an early modeling stage requires detailed cell geometry and specifications to estimate the thermal and electrochemical energies of the cell, module, and pack. To capture the dynamic performance changes of the LIB pack under real driving cycles, the thermal energy flow between the pack and its TMS must be well predicted. This study presents a BTMS model development and validation method for a 75-kWh battery pack used in mass-production, mid-size battery SUV under WLTC. Eighty thermocouples, pressure, and

Sok, Ratnak, Kishida, Kentaro, Otake, Tomohiro, Nandagopal, Kamaleshwar, Kusaka, Jin, Mizushima, Norifumi, Noyori, Takahiro

A Low-Cost System for Road Induced Tire Cavity Noise Control (RTNC

2024-01-2961To be published on 06/12/2024

The transition from ICE to electric power trains in new vehicles along with the application of advanced active and passive noise reduction solutions has intensified the perception of noise sources not directly linked to the propulsion system. This includes road noise as amplified by the tire cavity resonance. This resonance mainly depends on tire geometry, air temperature inside the tire and vehicle speed and is increasingly audible for larger wheels and heavier vehicles, as they are typical for current electrical SUV designs. Active technologies can be applied to significantly reduce narrow band tire cavity noise with low costs and minimal weight increase. Like ANC systems for ICE powertrains, they make use of the audio system in the vehicle. In this paper, a novel low-cost system for road induced tire cavity noise control (RTNC) is presented that reduces the tire cavity resonance noise inside a car cabin. The approach is cheap in terms of computational effort (likewise ICE engine

Sues, Micha, Nojavan, Aidin, Kirchhof, Jan, Schirmacher, Rolf

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