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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 January includes the following contents： 1. Article Recommendation——Three papers on intelligent and connected vehicles and electric vehicles 2. China SAE News: · Automotive Innovation Workshop is successfully held |
  
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VCANet: Vanishing-Point-Guided Context-Aware Network for Small Road Object Detection Guang Chen, Kai Chen, Lijun Zhang, Liming Zhang & Alois Knoll |
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| Advanced deep learning technology has made great progress in generic object detection of autonomous driving, yet it is still challenging to detect small road hazards in a long distance owing to lack of large-scale small-object datasets and dedicated methods. This work addresses the challenge from two aspects. Firstly, a self-collected long-distance road object dataset (TJ-LDRO) is introduced, which consists of 109,337 images and is the largest dataset so far for the small road object detection research. Secondly, a vanishing-point-guided context-aware network (VCANet) is proposed, which utilizes the vanishing point prediction block and the context-aware center detection block to obtain semantic information. The multi-scale feature fusion pipeline and the upsampling block in VCANet are introduced to enhance the region of interest (ROI) feature. The experimental results with TJ-LDRO dataset show that the proposed method achieves better performance than the representative generic object detection methods. This work fills a critical capability gap in small road hazards detection for high-speed autonomous vehicles. | |||
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Keywords: Autonomous driving, Road hazard, Object detection, Deep learning, Vanishing point Chen, G., Chen, K., Zhang, L. et al.: VCANet: Vanishing-Point-Guided Context-Aware Network for small road object detection. Automot. Innov. 4(4), 400–412 (2021) |
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An Innovative State-of-charge Estimation Method of Lithium-ion Battery Based on 5th-order Cubature Kalman Filter Huang Yi, Shichun Yang, Sida Zhou, Xinan Zhou, Xiaoyu Yan & Xinhua Liu |
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| The lithium-ion batteries have drawn much attention as the major energy storage system. However, the battery state estimation still suffers from inaccuracy under dynamic operational conditions, with the unstable environmental noise influencing the robustness of estimation. This paper presents a 5th-order cubature Kalman filter with improvements on adaptivity for real-time state-of-charge estimation. The second-order equivalent circuit model is developed for describing the characteristics of battery, and parameter identification is carried out according to particle swarm optimization. The developed method is validated in stable and dynamic conditions, and simulation results show a satisfactory consistency with the experimental results. The maximum estimation error under static conditions is less than 3% and the maximum error under dynamic conditions is 5%. Numerical analysis indicates that the method has better convergence and robustness than the traditional method under the disturbances of initial error, which demonstrates the potential for EV applications in harsh environments. The proposed method shows application potential for both online estimations and cloud-computing system, indicating its diverse application prospect in electric vehicles. | |||
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Keywords: 5th-order cubature Kalman filter, Parameter identification, Equivalent circuit model, State of charge, Lithium-ion battery
Yi, H., Yang, S., Zhou, S. et al.: An innovative state-of-charge estimation method of lithium-ion battery based on 5th-order Cubature Kalman Filter. Automot. Innov. 4(4), 448–458 (2021) |
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Design, Modeling, and Characterization of a Tubular Linear Vibration Energy Harvester for Integrated Active Wheel System Xin Wen, Yinong Li & Chao Yang |
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| A major source of electric vehicle energy loss is the vibration energy dissipated by the shock absorbers under irregular road excitation, which is particularly severe when active wheel systems are employed because their greater unsprung mass leads to greater shocks and vibrations. Therefore, a tubular linear energy harvester (TLEH) with a large stroke and low electromagnetic force ripple is designed to convert this vibration energy into electricity. The proposed TLEH employs a slotted external mover with three-phase winding coils and an internal stator with PMs to increase the stroke, adopts a fractional slot-per-pole configuration to reduce its size and improve the winding factor, and realizes significantly reduced cogging force by optimizing the incremental length of the armature core. A finite element model of the TLEH is first verified against a theoretical model and then used to investigate the influences of various road excitation frequencies and amplitudes on the electromotive force (EMF) waveforms and generated power, the efficiency and damping force according to load condition, and the energy recovery and nonlinear electromagnetic force characteristics of the TLEH. A resistance controller is then designed to realize a self-damping electromagnetic suspension. The results indicate that the EMF and the generated power waveforms depend on the excitation frequency and amplitude, the efficiency increases and the damping coefficient decreases with the increasing load resistance. | |||
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Keywords: Energy harvesting, Electric vehicles, Active wheel system, Self-damping suspension Wen, X., Li, Y. & Yang, C.: Design, modeling, and characterization of a tubular linear vibration energy harvester for integrated active wheel system. Automot. Innov. 4(4), 413–429 (2021) |
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| Automotive Innovation Workshop is successfully held | |||
 Automotive Innovation Workshop is successfully held online on Jan. 18, 2022. The workshop delivered a high-quality, international speaker line-up, which seeks to identify challenging problems facing the development of autonomous vehicles. It attracts over 33k viewers in the live-stream. Organized by: China SAE, Automotive Innovation Co-organized by: College of Automotive Engineering, Jilin University; State Key Laboratory of Automotive Simulation and Control Chair: Prof. Mike Ma, Executive Editor-in-Chief of Automotive Innovation, Technical Advisor of FISITA, Professor of Jilin University Co-chair: Prof. Xinjie Zhang, Executive Associate Editor-in-Chief of Automotive Innovation, Vice Director of State Key Laboratory of Automotive Simulation and Control, Professor of Jilin University  For detailed information, please click here. |
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| Jinhua Zhang: Trends in automotive technology convergence | |||
 Jinhua Zhang, Executive Vice President and Secretary General of China SAE, shares his views on the topic of "Trends in Automotive Technology Integration": Vehicles is developing based on integrating with the energy industry, intelligent and connected technologies and intelligent sharing. 1.The integration of vehicle and energy accelerates the transformation of vehicle electrification and promotes the energy industry to change from a supply-side-driven industry to a consumer-side-driven one. 2.Intelligent and connected vehicles is an inevitable result highly autonomous driving technology, which lays basis for 5G, AI, cloud computing and other new technologies. 3.Intelligent shared mobility will be the platform and hub for the new automotive industry ecology in the future, and will also power the new industry of digital economy and sharing economy. Looking into the future, the automotive industry urgently needs to break through the innovation boundary and realize the upgrading of the industry chain, innovation chain and value chain with the support of integrated innovation. The below efforts are needed: leading top-level strategy; building basis for technology innovation; landing scenario-driven applications; building innovation platform as support; empowering communication platform. Please click here to find out more. |
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| China Vehicle Production and Sales Analysis in 2021 | |||
 In 2021, China's vehicle production is 26.082 million and sales hit 26.275 million. China's total vehicle production and sales have ranked the first in the world for 13 consecutive years. The global vehicle production is 90.68 million, in which China contributes 28.8%; the global vehicle sales is 66 million, and China takes 39.8%. China's annual production of new energy vehicles is 3.545 million in 2021, and annual sales is 3.521 million. Global sales of new energy vehicles is 6.31 million units, with China accounting for 55.8%. Data source: China Association of Automobile Manufacturers, Statista |
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| SAECCE 2022 Call for Papers | |||
 The annual congress and exhibition of China SAE 2022 (SAECCE 2022) will be held in November 2022. With the theme of "Automobile Plus, Collaborative Innovation", SAECCE 2022 will focus on Electrification, Intelligence, Connected and Sharing, deeply discuss on how to quickly promote technological innovation and reshape the new industrial structure. SAECCE 2022 is now calling for papers. Submission Link http://www.saecce.org.cn/CN/essay/ Important Dates Deadline for paper submission: April 25, 2022 Paper acceptance notification: mid-July 2022 For more information, please click here . |
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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 19,000. The journal is indexed in Ei Compendex, ESCI, and Scopus. 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 Executive Editor-in-Chief Prof. Mike Ma，Executive Chief Editor of Automotive Innovation, Professor of Jilin University, VP Technical FISITA |
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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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