SAE Technical Paper Series最新文献

{"title":"Evaluation and Simulation of wheel Steering Functionality on a Road to Rig Test Bench","authors":"Lennart Kopp, Patrick Harfmann, Lucas Niederberger, Timm Schwämmle, Markus Kley","doi":"10.4271/2024-01-3000","DOIUrl":"https://doi.org/10.4271/2024-01-3000","url":null,"abstract":"The automotive industry is continuously evolving, demanding innovative approaches to enhance testing methodologies and preventively identify potential issues. This paper proposes an advanced test approach in the area of the overall vehicle system including the steering system and powertrain on a Road to Rig test bench. The research aims to revolutionize the conventional testing process by identifying faults at an early stage and eliminating the need to rely solely on field tests. The motivation behind this research is to optimize the test bench setup and bring it even closer to real field tests. Key highlights of the publication include the introduction of an expanded load spectrum, incorporating both steering angle and speed parameters along the test track. The load includes different route and driving profiles like on a freeway, overland and city drive in combination with the steering angles. Furthermore, for the first instance, specific driving manoeuvres, including slalom driving and autonomous parking, can now be simulated and tested. Also, there are critical driving scenarios like the standardized severe lane-change manoeuvre. This innovative approach not only refines the accuracy of steering simulations but also provides a comprehensive representation of real-world driving conditions. The paper also outlines the development and verification of a design specifically tailored for the test bench environment. This comprehensive approach ensures the reliability and applicability of the proposed steering simulation methodology. The integration of multibody simulations further enhances the study by elucidating the individual component loads.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"2 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation of Hydrogen Combustion in Spark Ignition Engines Using a Modified Wiebe Model","authors":"O. Osetrov, Rainer Haas","doi":"10.4271/2024-01-3016","DOIUrl":"https://doi.org/10.4271/2024-01-3016","url":null,"abstract":"Due to its physical and chemical properties, hydrogen is an attractive fuel for internal combustion engines, providing grounds for studies on hydrogen engines. It is common practice to use a mathematical model for basic engine design and an essential part of this is the simulation of the combustion cycle, which is the subject of the work presented here. One of the most widely used models for describing combustion in gasoline and diesel engines is the Wiebe model. However, for cases of hydrogen combustion in DI engines, which are characterized by mixture stratification and in some cases significant incomplete combustion, practically no data can be found in the literature on the application of the Wiebe model. Based on Wiebe’s formulas, a mathematical model of hydrogen combustion has been developed. The model allows making computations for both DI and PFI hydrogen engines. The parameters of the Wiebe model were assessed for three different engines in a total of 26 operating modes. The modified base model considers the significant incompleteness of hydrogen combustion, which occurs at high air/fuel equivalence ratio. For PFI and DI hydrogen engines, equations and numerical values for the Wiebe model coefficients were determined to describe the dynamic and duration of combustion. Based on our simulation results we suggest using the sum of two Wiebe curves to describe combustion in zones with a lean mixture in DI engines. This allows a more accurate characterization of the combustion dynamics and pressure curves. In order to model a double hydrogen injection, we suggest using the sum of three Wiebe curves representing the combustion of the first injection in the flame front, the diffusion combustion of the second injection, and the relatively slow combustion in lean mixture zones. In the paper, we present a method for selecting the coefficients of each of the Wiebe curves.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"154 6‐10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated AI-Based Annotation Framework for 3D Object Detection from LIDAR Data in Industrial Areas","authors":"Gina Abdelhalim, Kevin Simon, Robert Bensch, Sai Parimi, Bilal Ahmed Qureshi","doi":"10.4271/2024-01-2999","DOIUrl":"https://doi.org/10.4271/2024-01-2999","url":null,"abstract":"Autonomous Driving is used in various settings, including indoor areas such as industrial halls and warehouses. For perception in these environments, LIDAR is currently very popular due to its high accuracy compared to RADAR and its robustness to varying lighting conditions compared to cameras. However, there is a notable lack of freely available labeled LIDAR data in these settings, and most public datasets, such as KITTI and Waymo, focus on public road scenarios. As a result, specialized publicly available annotation frameworks are rare as well. This work tackles these shortcomings by developing an automated AI-based labeling tool to generate a LIDAR dataset with 3D ground truth annotations for industrial warehouse scenarios. The base pipeline for the annotation framework first upsamples the incoming 16-channel data into dense 64-channel data. The upsampled data is then manually annotated for the defined classes and this annotated 64-channel dataset is used to fine-tune the Part-A2-Net that has been pretrained on the KITTI dataset. This fine-tuned network shows promising results for the defined classes. To overcome some shortcomings with this pipeline, which mainly involves artefacts from upsampling and manual labeling, we extend the pipeline to make use of SLAM to generate the dense point cloud and use the generated poses to speed up the labeling process. The progression, therefore shows the three generations of the framework which started with manual upsampling and labeling. This then was extended to a semi-automated approach with automatic generation of dense map using SLAM and automatic annotation propagation to all the scans for all static classes and then the complete automatic pipeline that generates ground truth using the Part-A2-Net which was trained using the dataset generated from the manual and semi-automated pipelines. The dataset generated for this warehouse environment will continuously be extended and is publicly available at https://github.com/anavsgmbh/lidar-warehouse-dataset.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"55 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardized Differential Inductive Positioning System for Wireless Charging of Electric Vehicles","authors":"Mike Boettigheimer, Philip Grabherr","doi":"10.4271/2024-01-2987","DOIUrl":"https://doi.org/10.4271/2024-01-2987","url":null,"abstract":"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 generated within the GA. On the VA induced voltages by the standardized magnetic fields are measured with two crossed coils. A dedicated coil in the GA provides the (magnetic) field for the steering and braking information. The stop signal for the vehicle is provided by an array of four coils in the GA. Additionally to private garages, the DIPS is designed for multi-GA parking spots as well. The special differential signal processing makes the procedure extremely robust against metallic foreign objects. The high accuracy of the DIPS allows the driver to align the vehicle at the first attempt. The automized pairing process enables a charging process without interaction of the driver.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"355 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electromagnetic Compatibility Assessment of Electric Vehicles during DC-Charging with European Combined Charging System","authors":"Inti Runa Supa Stölben, M. Beltle, Stefan Tenbohlen","doi":"10.4271/2024-01-3008","DOIUrl":"https://doi.org/10.4271/2024-01-3008","url":null,"abstract":"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 minimise losses and improve efficiency, but it might also generate electro-magnetic 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 61851-21-2. This paper presents possible test setups supporting the standard. Furthermore, it emphasizes the need for measurements not only in controlled laboratories, but also at real charging stations within their specific environments. Therefore, a mobile test setup is introduced and validated. It can be connected to any public DC charging station using a European standard plug CCS-2 (Combined Charging System 2). In addition, the emerging concept of Vehicle to Grid (V2G) is gaining prominence. The objective is to leverage electric vehicles as mobile energy storage for grid optimization and stabilization. The proposed test setup also allows to take these operating states into account concerning conducted interference emissions. As the transition to electric mobility progresses, these investigations contribute ensuring the seamless integration of EVs into the evolving energy landscape.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"33 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated Park and Charge: Concept and Energy Demand Calculation","authors":"Axel Sturm, M. Kascha, M. A. Mejri, Roman Henze, L. Heister, A. Mueck","doi":"10.4271/2024-01-2988","DOIUrl":"https://doi.org/10.4271/2024-01-2988","url":null,"abstract":"In this paper, we present the concept of automated park and charge functions in two different use cases. The main use case is automated driving in production and the other use case is within automated valet parking in parking garages. The automated park and charge in production is developed in the scope of the publicly funded project E-SELF in Germany. The central aim of this 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 motion 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 the end-of-line. In addition, long shipping, combined with a specific state of charge requirement at customer delivery, require recharging at the production facility. This recharging process is also an automated process with a robot and demands direct connection to the driving function. The main scope of this paper is the introduction of an energy demand calculation for the necessary charging operations. The developed tool allows multiple analyses for identifying further potentials in the production line. Based on a study of a Ford Mach-E it showed, that the highest energy demands are due to battery self-discharging during standstill, especially in the summer months. For a transport to the customer by train and truck, an energy demand of 2kWh within the production facility is estimated. Longer transport times, e.g. when the vehicle is shipped to the customer, the energy demand increases up to 4 kWh. Depending on the vehicle and application, the developed toolchain allows future optimization of recharging processes and also promotes automated park and charging, where the demands can be individually calculated by the park management system.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"333 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141686915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of Stator Cooling Concepts of an Electric Machine for Maximization of Continuous Power","authors":"Mike Reinecke, Akif Karayel, Hendrik von Schöning, Uwe Schaefer, M. Moullion, Victor Faessler, R. Lehmann","doi":"10.4271/2024-01-3014","DOIUrl":"https://doi.org/10.4271/2024-01-3014","url":null,"abstract":"With the automotive industry’s increasing focus on electromobility and the growing share of electric cars, new challenges are arising for the development of electric motors. The requirements for torque and power of traction motors are constantly growing, while installation space, costs and weight are increasingly becoming limiting factors. Moreover, there is an inherent conflict in the design between power density and efficiency of an electric motor. Thus, a main focus in today’s development lies on space-saving and yet effective and innovative cooling systems. This paper presents an approach for a multi-physical optimization that combines the domains of electromagnetics and thermodynamics. Based on a reference machine, this simulative study examins a total of nine different stator cooling concepts varying the cooling duct positions and end-winding cooling concepts. To ensure the highest possible comparability, the rotor geometry as well as the overall dimensions in terms of outer diameter and length of the electric machine remain unchanged. The stator design is slightly adjusted to achieve same maximum torque and winding cross-section. Initially, the electromagnetic effects of various cooling slot positions are investigated and compared with respect to efficiency and individual loss distribution. Subsequently, the thermal performance is analyzed by means of fluid-dynamical simulations to quantify the heat transfer and assess the cooling effectivity. Eventually, these results are merged in a lumped parameter thermal network model. Accounting for both the distinguished electromagnetic and thermal benefits and disadvantages, a final study is presented evaluating the continuous power capability of the different concepts at equal boundary conditions.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"6 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141687300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal Management System for Battery Electric Heavy-Duty Trucks","authors":"Daniel Gajowski, Wolfgang Wenzel, Matthias Hütter","doi":"10.4271/2024-01-2971","DOIUrl":"https://doi.org/10.4271/2024-01-2971","url":null,"abstract":"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. Meanwhile, the first generation of a complete portfolio of truck sizes has been developed and is available on the market. In these early applications, many compromises were made to overcome component availability, but today, the supply chain has evolved to address the specific needs of electric trucks. With that, optimization toward higher performance and lower costs is moving to the next level. For long-haul trucks, efficiency is a driving factor for the total cost of ownership (TCO) due to the importance of the energy costs [1]. Besides the propulsion system, other related 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 of thermal management is to protect the components to ensure a long lifetime, especially in the case of the battery. The driver's comfort is another important purpose of the thermal management system (TMS). In the present study, the design development of the TMS layout for an electric heavy-duty (HD) truck is described. The modeled TMS is challenged under different operation conditions, including demanding drive cycles as well as fast charging events. The results are analyzed in terms of energy flows and the usage of the different components of the thermal system. From those results, conclusions are derived for the sizing of components to meet the requirements of electric HD truck applications.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"72 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141688680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal and Prototype Dimensioning of Electrified Drives for Automated Driving","authors":"Axel Sturm, Gerrit Brandes, Marcel Sander, Roman Henze, F. Küçükay","doi":"10.4271/2024-01-3021","DOIUrl":"https://doi.org/10.4271/2024-01-3021","url":null,"abstract":"Electrified drives will change significantly in the wake of the further introduction of automated driving functions. Precise drive dimensioning, taking automated driving into account, opens up further potential in terms of drive operation and efficiency as well as optimal component design. Central element for unlocking the dimensioning potentials is the knowledge about the driving functions and their application. In this paper the implications of automated driving on the drive and component design are discussed. A process and a virtual toolchain for electric drive development from concept optimization to detailed dimensioning validation is presented. The process is subdivided into a concept optimization part for finding the optimal drive topology and layout and a detailed prototype environment, where more detailed component models can be assessed in customer operation to enable representative component dimensioning. Furthermore, the detailed simulation allows the drive investigation in representative customer operation as well as automated driving functions in terms of a software in the loop simulation. The process is used for the optimal dimensioning of a battery electric vehicle of the D-segment. The work focusses on a highway pilot function, developed at the Institute of Automotive Engineering of the Technische Universität Braunschweig. The optimal drive configuration can later be transferred to the prototype dimensioning. The simulation of automated driving function operation is based on a vehicle following scenario which employs statistical human behavior in the target vehicle and a sliding mode ACC in the ego vehicle. This methodology is particularly suitable for determining load spectra, which in turn can be used as test specifications for the strength simulation or endurance testing of the electric drive. Furthermore, simulation results can be used for the definition of representative cycles applicable for the concept optimization. The results of both processes will be compared and discussed in detail with an emphasis on efficiency, performance and load spectra.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"2 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141684870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cybersecurity Approval Criteria: Application of UN R155","authors":"Mona Hellstern, Stefan Langhanki, Florian Grün, Reiner Kriesten, Eric Sax","doi":"10.4271/2024-01-2983","DOIUrl":"https://doi.org/10.4271/2024-01-2983","url":null,"abstract":"The UN R155 regulation is the first automotive cybersecurity regulation and has made security a mandatory approval criterion for new vehicle types. This establishes internationally harmonized security requirements for market approval, presenting a challenge for manufacturers and suppliers to demonstrate compliance throughout the product life cycle. 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. Independent accredited assessors assess the security engineering results during type approval. Considering the risk-based approach of ISO/SAE 21434 to security engineering, assessing whether threats have been appropriately addressed is a challenge. While there are currently no uniform assessment criteria at product level, the question arises as to which development artifacts serve as indicators for determining the efficacy of mitigation strategies. In response to this challenge, the paper conducts an analysis of existing security concepts of the automotive security standard ISO/SAE 21434 and the Information Technology Security Evaluation Standard ISO 15408 (Common Criteria) and therefore provides an insight into the state-of-the-art of security evaluation methods. The overall objective is to derive applicable assessment criteria and recommendations for the UN R155 approval while taking into account relevant security properties that help to decide on the sufficiency of security measures. These recommendations aim to enhance the comprehensiveness of the security assessment associated with UN R155, fostering a more uniform approach to evaluating cybersecurity in the context of vehicle type approvals.","PeriodicalId":510086,"journal":{"name":"SAE Technical Paper Series","volume":"22 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141685767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}