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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. A Glimpse of Experts——Dr. Chen Lv from Nanyang Technological University, Singapore 2. Article Recommendation——Four papers on technologies of hybrid vehicle, engine and dynamics 3. China SAE News: · H2 Corridor Development Plan in the Yangtze River Delta Region was officially released |
 Dr. Chen Lv Assistant Professor, Nanyang Technological University, Singapore Director of Automated Driving and Human-Machine Systems Group Cluster Director in Intelligent Electrified Vehicles in ERI@N |
Research Interests and Expertise Automated Driving, Human-Machine Collaboration, Intelligent Electric Vehicles |
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Profile He received the Ph.D. degree from the School of Vehicle and Mobility, Tsinghua University, China. He was a joint PhD researcher at UC Berkeley, USA, and a Research Fellow at Cranfield University, UK. He joined Nanyang Technological University (NTU) as an assistant professor and founded the Automated Driving and Human-Machine System (AutoMan) Research Group in June 2018. His research focuses on advanced vehicle control and intelligence, where he has contributed 1 book, 2 book chapters, over 80 papers and obtained 12 granted patents. He received the Highly Commended Paper Award of IMechE UK in 2012, the China SAE Outstanding Paper Award in 2015, the 1st Class Award of China Automotive Industry Scientific and Technological Invention in 2015, the Tsinghua Outstanding Doctoral Thesis Award in 2016, the Seal of Excellence of EU H2020 Marie Skłodowska-Curie Actions in 2017, the Young Elite Scientist of CAST in 2017, the Best Workshop/Special Session Paper Award of IEEE Intelligent Vehicle Symposium in 2018, and CSAE Outstanding Doctoral Dissertation Award in 2018. He serves as a Guest Editor for IEEE/ASME Transactions on Mechatronics, IEEE Transactions on Industrial Informatics, Applied Energy, and IJPT, and an Editor for Automotive Innovation, Frontiers in Mechanical Engineering, and International J. of Electric and Hybrid Vehicle. |
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Perspective: challenges and development trends for intelligent electric vehicles Intelligent electric vehicles, which combine the vehicle electrification and intelligence, become a collaborative innovation platform for the development of new energy and autonomous vehicle technologies. Besides, the intervention of driver behavior further makes it a multi-disciplinary complex system through human-vehicle interactions. These bring more opportunities for vehicle performance improvement, however, they also pose great challenges to the existing theories and methods for vehicle design and control. Therefore, it is needed to further explore the co-design optimization methodology of human-cyber-vehicle systems, to enable the collaborative innovations in multi-disciplinary automotive technologies. |
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Driving-Cycle-Aware Energy Management of Hybrid Electric Vehicles Using a Three-Dimensional Markov Chain Model Bolin Zhao, Chen Lv, Theo Hofman |
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| This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy management strategy. The impacts of different prediction time lengths on driving cycle generation were explored. The results indicate that the original driving cycle is compressed by 50%, which significantly reduces the computational burden while having only a slight effect on the prediction performance. The developed driving cycle prediction method was implemented in a real-time energy management algorithm with a hybrid electric vehicle powertrain model, and the model was verified by simulation using two different testing scenarios. The testing results demonstrate that the developed driving cycle prediction method is able to efficiently predict future driving tasks, and it can be successfully used for the energy management of hybrid electric vehicles. | |||
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Keywords: Driving cycle prediction · Markov chain model · Hybrid electric vehicles · Energy management Zhao, B., Lv, C., and Hofman, T.: Driving-cycle-aware energy management of hybrid electric vehicles using a three-dimensional Markov chain model. Automotive Innovation 2(2): 146-156 (2019) |
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A Review of Engine Fuel Injection Studies using Synchrotron Radiation X-ray Imaging Zhijun Wu, Wenbo Zhao, Zhilong Li, Jun Deng, Zongjie Hu, Liguang Li |
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| Fuel spray characteristics directly determine the formation pattern and quality of the fuel/air mixture in an engine, and thus affect the combustion process. For this reason, the improvement and optimization of fuel injection systems is crucial to the development of engine technologies. The fuel jet breakup and atomization process is a complex liquid-gas two-phase turbulent flow system that has not yet been fully elucidated. Owing to the limitations of standard optical measurement techniques, the spray breakup mechanism and its interaction with the nozzle internal flow are still unclear. However, in recent years synchrotron radiation (SR) X-ray imaging technologies have been widely applied in engine fuel injection studies because of the higher energy and brilliance of third-generation SR light sources. This review provides a brief introduction to the development of SR technology and compares the critical parameters of the primary third-generation SR light sources available worldwide. The basic principles and applications of various X-ray imaging technologies with regard to nozzle internal structure measurements, visualization of in-nozzle flow characteristics and quantitative analyses of near-field spray transient dynamics are examined in detail. | |||
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Keywords: X-ray imaging technology · Fuel injection · Nozzle internal structure · In-nozzle flow visualization · Near-field spray dynamics Wu, Z., Zhao, W., Li, Z., et al.: A review of engine fuel injection studies using synchrotron radiation x-ray imaging. Automotive Innovation 2(2): 79-92 (2019) |
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State Estimation of Vehicle’s Dynamic Stability Based on the Nonlinear Kalman Filter Xiaofei Pei, Xu Hu, Wei Liu, Zhenfu Chen, Bo Yang |
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| An accurate estimation of a vehicle’s state of motion is the basis of dynamic stability control. Two different nonlinear Kalman filters are adopted for the estimation of the vehicle’s lateral/rollover stability state. First, the overall structure of the state estimation with four inputs and four outputs is introduced. After determining tire-cornering stiffness using a recursive least-squares (RLS) method, the equations of state and of observation for the nonlinear Kalman filter are established based on a vehicle model with four degrees of freedom including planar and rollover dynamics. Then, the specific steps of real-time state estimation using the extended Kalman filter (EKF) and unscented Kalman filter (UKF) are both given. In a co-simulation, we find that the RLS algorithm estimates tire-cornering stiffness accurately and quickly, and the UKF improves the effect of state estimation compared with EKF. In addition, the UKF is verified against data from vehicle tests. The results show the proposed method is reliable and practical in estimating vehicle states. | |||
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Keywords: Vehicle dynamic · State estimation · EKF · UKF · Vehicle test Pei, X., Hu, X., Liu, W., et al.: State estimation of vehicle’s dynamic stability based on the nonlinear Kalman filter, Automotive Innovation 1(3), 281-289(2018) |
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Mechanism and Conditions of the Polygonal Wear of Vehicle Tire Shuguang Zuo, Tianxin Ni, Xudong Wu, Yong Li, Xianwu Yang |
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| Polygonal wear seriously decreases the lifespan of a tire of a passenger car and adversely affects vehicle dynamic safety. The present paper builds a model that reflects the dynamic contact characteristics of the tire and reveals the mechanism and conditions of polygonal wear of a tire. The model describes the dynamic contact behavior of the tread block and considers the characteristics of dynamic friction between the road and tread of a rolling tire. Conducting numerical bifurcation analysis, the paper reveals the conditions for self-excited vibration of the tread, i.e., the improper combination of the vertical load, wheel slip angle, tire pressure and vehicle speed considerably strengthen the lateral self-excited vibration of the tread, which is the direct vibrational source of abnormal circumferential polygonal wear. The polygonal wear of a tire occurs when a vehicle travels for a certain long distance at a so-called polygonal wear speed. The polygonal wear speed should induce lateral self-excited vibration on the contact tread of the tire and the frequency of the lateral self-excited vibration should be divisible by the rolling frequency of tire that is determined by the polygonal wear speed. Visible polygonal wear requires that the vehicle travels at a certain polygonal wear speed for a minimal distance to produce a stably developing polygonal wear pattern even for subsequent driving at variable speed. | |||
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Keywords: Tire polygonal wear · Tread contact model · Self-excited vibration · Wear calculation · Bifurcation analysis Zuo, S., Ni, T., Wu, X., et al.: Mechanism and conditions of the polygonal wear of vehicle tire, Automotive Innovation 1(2), 167-176(2018) |
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| H2 Corridor Development Plan in the Yangtze River Delta Region was officially released | |||
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The Hydrogen Corridor Construction and Development Plan in the Yangtze River Delta Region (the "Plan") was released in Shanghai on May 24th, 2019. The plan was developed by the China Society of Automotive Engineers (China SAE), under the guidance of the newly established Yangtze River Delta Regional Cooperation Office – the joint administrative office responsible for the integrated development of the Yangtze River Delta Region, which includes Shanghai and three provinces (Jiangsu, Zhejiang & Anhui) with a combined $2.5 trillion GDP accounting for almost 20% of China's total GDP.
According to the plan, over the next three years, China will develop 10 hydrogen refueling stations (HRS) along four express highways connecting Shanghai with four major cities (Rugao, Suzhou, Huzhou & Ningbo) in the Yangtze River Delta region. By the end of 2030, the region is projected to build 500+ HRSs and deploy 200,000+ FCVs. For more information on this plan, please visit http://www.ihfca.org.cn/a3002.html. |
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| Revision work of Technology Roadmap for Energy Saving and New Energy Vehicles will start | |||
| The kick off meeting of the revision of Technology Roadmap for Energy Saving and New Energy Vehicles was held in Beijing on May 28, 2019. The "Technology Roadmap for Energy Saving and New Energy Vehicles " was officially released in 2016, which embodies the wisdom and consensus of more than 1,000 experts in automotive and related industries. It’s a significant reference book to guide the development of automotive technology, and plays an important role in promoting the healthy and sustainable development of the industry. The revision version of this book will expand from "1+7" to "1+9", that is, an overall research plus energy-saving vehicles, EV & HEV, ICV, FCV, new energy electric drive systems, charging infrastructure, power battery, lightweight technology and intelligent manufacturing. It’s expected to be completed and officially published in the first half of 2020. | |||
| 2019 World Fuel Cell Conference is calling for papers | |||
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Organized by IAHE Fuel Cell Division, 2019 World Fuel Cell Conference will be held in Shanghai, China on August 25-29, 2019. Abstracts/Papers are sought in all areas of Fuel Cell Technology, including but not limited to Fuel Cell, hydrogen and Inter-connection. Some selected papers, after proper respective review, will be recommended for publication in special issues of several prestigious international journals, including Automotive Innovation.
The deadline for abstract submission is July 12, 2019. For more information, please visit the website http://www.iahe-fcd.org/. |
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Automotive Innovation Automotive Innovation is the first English journal in China's automotive industry. Founded in 2018, sponsored by China SAE and published via Springer, Automotive Innovation has a very special significance in China's automotive academia. Since its foundation, world-renowned automotive experts with high H index have been invited to join the editorial board, and the strict standards of SCI Journals are meticulously followed to ensure the high quality of papers and publication. By now, six issues have been published successfully with readers in 72 countries and regions. Many famous professors have already published articles in it, such as Prof. Liguang Li, Prof. Shijin Shuai, Prof. Ferit Küçükay, Prof. Xiangyang Xu, Prof. Amir Khajepour and so on. The journal has been recognized by FISITA, other international organizations and some well-known universities. Editors-in-Chief Jun Li, Academician of CAE, President of China SAE, Professor of Tsinghua University Frank Zhao, President (2018-2020) of FISITA, President of Tsinghua Automotive Strategy Research Institute 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. Huisi, Gu Tel: +86-10-50950101 Email: ghs@sae-china.org |
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