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The journal Automotive Innovation is sponsored by China SAE, published through Springer, distributed around the world, and reflects the top-level research and technical advance of automotive engineering. Automotive Innovation newsletter in June includes the following contents： 1. Article Recommendation——Four papers on Autonomous Vehicles and Electric Vehicles 2. China SAE News: · ISC 2022 registration starts |
  
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Impact, Challenges and Prospect of Software-Defined Vehicle Zongwei Liu, Wang Zhang & Fuquan Zhao |
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| Software-defined vehicles have been attracting increasing attentions owing to their impacts on the ecosystem of the automotive industry in terms of technologies, products, services and enterprise coopetition. Starting from the technology improvements of software-defined vehicles, this study systematically combs the impact of software-defined vehicles on the value ecology of automotive products and the automotive industrial pattern. Then, based on the current situation and demand of industrial development, the main challenges hindering the realization of software-defined vehicles are identified, including that traditional research and development models cannot adapt to the iterative demand of new automotive products; the transformation of enterprise capability faces multiple challenges; and many contradictions exist in the industrial division of labor. Finally, suggestions are put forward to address these challenges and provide decision-making recommendations for enterprises on strategy management. | |||
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Keywords: Software-defined vehicle · Industrial reconstruction · Automotive industry · Strategic suggestions Liu, Z., Zhang, W. & Zhao, F.: Impact, challenges and prospect of software-defined vehicles. Automot. Innov. 5(2), 180–194 (2022) |
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Autonomous Overtaking for Intelligent Vehicles Considering Social Preference Based on Hierarchical Reinforcement Learning Hongliang Lu, Chao Lu, Yang Yu, Guangming Xiong & Jianwei Gong |
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| As intelligent vehicles usually have complex overtaking process, a safe and efficient automated overtaking system (AOS) is vital to avoid accidents caused by wrong operation of drivers. Existing AOSs rarely consider longitudinal reactions of the overtaken vehicle (OV) during overtaking. This paper proposed a novel AOS based on hierarchical reinforcement learning, where the longitudinal reaction is given by a data-driven social preference estimation. This AOS incorporates two modules that can function in different overtaking phases. The first module based on semi-Markov decision process and motion primitives is built for motion planning and control. The second module based on Markov decision process is designed to enable vehicles to make proper decisions according to the social preference of OV. Based on realistic overtaking data, the proposed AOS and its modules are verified experimentally. The results of the tests show that the proposed AOS can realize safe and effective overtaking in scenes built by realistic data, and has the ability to flexibly adjust lateral driving behavior and lane changing position when the OVs have different social preferences. | |||
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Keywords: Automated overtaking system · Semi-Markov decision process · Hierarchical reinforcement learning · Social preference
Lu, H., Lu, C., Yu, Y. et al.: Autonomous overtaking for intelligent vehicles considering social preference based on hierarchical reinforcement learning. Automot. Innov. 5(2), 195–208 (2022) |
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Structural Topology and Dynamic Response Analysis of an Electric Torque Vectoring Drive-Axle for Electric Vehicles Junnian Wang, Shoulin Gao, Yue Qiang, Meng Xu, Changyang Guan & Zidong Zhou |
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| In-wheel motor-drive electric vehicles have the advantage of independently controllable wheel torque and the disadvantages of unsprung mass rise and power restriction. To address the disadvantages, a centralized layout electric torque vectoring drive-axle system (E-TVDS) with dual motors is proposed, which can realize arbitrary distribution of driving torque between the left and right wheels. First, the speed and torque distribution principle of E-TVDS based on velocity diagram are analyzed, and a virtual prototype of the whole vehicle with basic gear ratio relation model of the E-TVDS is built for simulation to verify the theoretical results and the basic effect of E-TVDS on the steering performance of the vehicle. Second, the characteristics of 36 types of the novel E-TVDS topology structure are compared and analyzed, and the optimal structure scheme is selected. Third, the accurate multiple degrees of freedom dynamic model for the optimal structure is established by using the bond graph method, and its dynamic response characteristics are analyzed. The results show that the vehicle equipped with the proposed E-TVDS can distribute the driving torque with the almost identical amount but opposite sign between the left and right wheels in any direction, and varying amount according to different chassis dynamics control requirements, and the torque response performance is great with little delay and overshoot. The function and dynamic response of the proposed E-TVDS show that it has potential application value for various performance improvements of electric vehicles. | |||
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Keywords: Electric vehicle · Torque vectoring · Differential · Structural topology · Bond graph Wang, J., Gao, S., Qiang, Y. et al.: Structural topology and dynamic response analysis of an electric torque vectoring drive-axle for electric vehicles. Automot. Innov. 5(2), 164–179 (2022) |
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Energy Security Planning for Hydrogen Fuel Cell Vehicles in Large-Scale Events: A Case Study of Beijing 2022 Winter Olympics Pinxi Wang, Qing Xue, Jun Yang, Hao Ma, Yilun Li & Xu Zhao |
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| Energy security planning is fundamental to safeguarding the traffic operation in large-scale events. To guarantee the promotion of green, zero-carbon, and environmental-friendly hydrogen fuel cell vehicles (HFCVs) in large-scale events, a five-stage planning method is proposed considering the demand and supply potential of hydrogen energy. Specifically, to meet the requirements of the large-scale events’ demand, a new calculation approach is proposed to calculate the hydrogen amount and the distribution of hydrogen stations. In addition, energy supply is guaranteed from four aspects, namely hydrogen production, hydrogen storage, hydrogen delivery, and hydrogen refueling. The emergency plan is established based on the overall support plan, which can realize multi-dimensional energy security. Furthermore, the planning method is demonstrative as it powers the Beijing 2022 Winter Olympics as the first “green” Olympic, providing both theoretical and practical evidence for the energy security planning of large-scale events. This study provides suggestions about ensuring the energy demand after the race, broadening the application scenarios, and accelerating the application of HFCVs. | |||
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Keywords: Li-ion battery · State of health · Gaussian process regression · Kernel function · Feature optimization Wang, P., Xue, Q., Yang, J. et al.: Energy security planning for hydrogen fuel cell vehicles in large-scale events: a case study of Beijing 2022 Winter Olympics. Automot. Innov. 5(2), 209–220 (2022) |
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| ISC 2022 registration starts | |||
 China SAE and FISITA are delighted to confirm that the FISITA Intelligent Safety Conference 2022 (ISC 2022) will take place 30-31 August 2022, in Beijing, China, with physical and online participation available to registered participants. ISC 2022 will again see an international speaker line up considering some of the most important topics within the safety of future mobility arena, including SOTIF, Test and Evaluation, Cybersecurity, Human Factors, and Smart Safety Protection. The registration for ISC 2022 has started, and we look forward to your participation. Registration: http://meeting.sae-china.org/ISC2022/ Conference website: www.fisita.com/isc |
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| Call for Papers: Special Issue on Environmentally Benign Automotive Lightweighting | |||
 Guest Editors: · Prof. Junying Min, School of Mechanical Engineering, Tongji University · Prof. A. Erman Tekkaya, Institute of Forming Technology and Lightweight Components, TU Dortmund University · Prof. Yongbing Li, School of Mechanical Engineering, Shanghai Jiao Tong University · Prof. Yannis P. Korkolis, Department of Integrated Systems Engineering, The Ohio State University · Ass. Prof. Ying Zhao, Southwest University Topics: · Energy and resource efficiency, CO2-footprint and recyclability of multi-material systems · Mechanical behaviours and microstructural evolution of automotive lightweight materials · Novel design and optimization algorithms of automotive lightweight structures · Forming and joining processes of single- and multi-material lightweight automobiles Submission deadline: Dec. 15, 2022 Submit at: www.springer.com/42154 To download call for paper, please click here. |
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| TMC 2022 is to be held on Aug. 8-9 in Qingdao | |||
 The 14th Transmission symposium China (TMC2022) will be held on Aug. 8-9, 2022 in Qingdao. More industry leaders, executives and experts will be invited to introduce and discuss the innovative technologies and strategies of electrified and intelligent powertrains. TMC2022 is expected to assemble 60-75 speeches from industry leaders, executives and experts, 3-4 high-level panel discussion on hot issues, more than 90 exhibitors and 1000 professional participants. The registration has started, please click here for further information. |
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Automotive Innovation Sponsored by China SAE and published globally via Springer Nature, Automotive Innovation aims to be a world-class journal that provides abundant sources of innovative findings for automotive engineers and scientists. The journal is published quarterly, ensuring high-quality papers satisfying international standards. With the editorial board consisting of world-renowned experts, it has attracted readers from 72 countries and regions. The highest download of a single article wins more than 21,000. The journal is indexed in Ei Compendex, ESCI, and Scopus (CiteScore=3.2). The journal provides a forum for the research of principles, methodologies, designs, theoretical background, and cutting-edge technologies in connection with the development of vehicle and mobility. The main topics cover: energy-saving, electrification, intelligent and connected, safety, and emerging vehicle technologies. Editors-in-Chief Jun Li, Academician of CAE, President of China SAE, Professor of Tsinghua University Frank Zhao, Honorary Lifetime President of FISITA, Director of Tsinghua Automotive Strategy Research Institute, Professor of Tsinghua University Honorary and Founding Executive Editor-in-Chief Prof. Fangwu (Mike) Ma Executive Associate Editor-in-Chief Prof. Xinjie Zhang, Professor of Jilin University |
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Paper submission and browse www.ChinaSAEJournal.com.cn www.springer.com/42154 Contacts: Ms. Lily Lu Tel: +86-10-50950101 Email: jai@sae-china.org 
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