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In China, nearly 25% of traffic fatalities are pedestrians. To avoid those fatalities in the future, rapid development of countermeasures within both passive and active safety is under way, one of which is autonomous braking to avoid pedestrian crashes. The objective of this work was to describe typical accident scenarios for pedestrian accidents in China. In-depth accident analysis was conducted to support development of test procedures for assessing Autonomous Emergency Braking (AEB) systems. Beyond that, this study also aims for estimating the mitigation of potential crash severity by AEB systems. The China In-depth Accident Study (CIDAS) database was searched from 2011 to 2014 for pedestrian accidents. A total of 358 pedestrian accidents were collected from the on-site in-depth investigation in the first phase of CIDAS project (2011-2014).

In recent years, with the rapid development of new energy vehicles, the impact of electromagnetic field (EMF) from vehicles to human body has become a growing concern of consumers. The national standard GB/T 37130-2018 "Measurement methods for electromagnetic field of vehicle with regard to human exposure" was officially released at the end of 2018, which was attracted extensive attention of vehicle manufacturers, testing structures and consumers. GB/T 37130-2018 specifies the test methods for low frequency EMF of vehicles.

Most of the Advanced Driver Assistance System (ADAS) applications are aiming at improving both driving safety and comfort. Understanding human drivers' driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system performance, in particular, the acceptance and adaption of ADAS to human drivers. The research presented in this paper focuses on the classification and identification for personalized driving styles. To motivate and reflect the information of different driving styles at the most extent, two sets, which consist of six kinds of stimuli with stochastic disturbance for the leading vehicles are created on a real-time Driver-In-the-Loop Intelligent Simulation Platform (DILISP) with PanoSim-RT®, dSPACE® and DEWETRON® and field test with both RT3000 family and RT-Range respectively.

With the development of electric vehicles (EVs), hybrid electric vehicles (HEVs) and fuel cell vehicles (FCVS), high voltage and large-current are applied to cables. Therefore, it is important to avoid electromagnetic compatibility (EMC) problems of cables, and a measurement methods is necessary for the shielding effectiveness of shielding cables. This paper discusses the existing test methods of cable shielding effectiveness and summarizes the main problems and deficiencies. Then, according to the practical requirements of high voltage cable testing, the direct injection method based on the national standard GB/T 18655-2018 (modified international standard CISPR 25) is proposed. The test method is verified by constructing a practical test platform.

To restrain the environmental and energy problems caused by oil consumption and improve fuel economy of heavy-duty commercial vehicles, China started developing relevant standards from 2008. This paper introduces the background and development of China's national standard “Fuel consumption test methods for heavy-duty commercial vehicles”, and mainly describes the test method schemes, driving cycle and weighting factors for calculating average fuel consumption of various vehicle categories. The standard applies to heavy-duty vehicles with the maximum design gross mass greater than 3500 kg, including semi-trailer tractors, common trucks, dump trucks, city buses and common buses. The standard adopts the C-WTVC driving cycle which is adjusted on the basis of the World Transient Vehicle Cycle[1, 2] and specifies weighting factors of urban, rural and motorway segments for different vehicle categories.

A vehicle’s NVH performance has a significant impact on the user experience of the driver and passengers. About one-third of the vehicle complaints are related to NVH performance. As the core component of the vehicle, the drivetrain’s NVH characteristics have a significant impact on vehicle comfort. How to reliably and stably reproduce the specific condition of the whole vehicle through the test method, and obtain the highly consistent objective data for analyzing and improving the NVH characteristics of the drivetrain is of great significance in engineering. For this purpose, China Automotive Technology Research Center Co., Ltd. (CATARC) designed and built a new type drivetrain NVH test facility, which consists of five dynamometers, and can carry horizontal/vertical, front/rear drive or four-wheel drive structures including powertrain, transmission, and rear axle, or even a whole vehicle.

Battery management system (BMS) is the core component of the new energy vehicle battery system. With the increase of energy density of new energy vehicle battery, its control algorithm becomes more and more complex, and the work of the battery management system will be heavier. In order to solve the limits, the hardware, software and control strategy model of battery management system are developed based on AURIX multi-core microcontroller. The microprocessor control unit is developed by using dual-core chip, which meets the functional safety requirements. Dual-core processing of control strategy and individual information acquisition are realized, and the processing efficiency is improved. A four-tier software architecture of battery management system is developed to handle the Dual-core processing. The graphical development of battery management system strategy model is realized by using MATLAB / Simulink.

This paper presents a HiL test bench specifically designed for closed-loop testing of the monocular-vision based ADAS sensors, whereby the animated pictures of the virtual scene is calibrated and projected onto a 120-degree circular screen, such that the camera sensor installed has the same vision as the observation of the real-world scene. A high-fidelity AEBs model is established and deployed in the real-time target of the HiL system, making intervention decisions based on the instance-level detection information transmitted from the physical sensor. By referring to the 2018 edition of the C-NCAP testing protocol, the HiL tests of the rear-end collision scenarios is performed to investigate the performance and characteristics of the longitudinal-motion sensing of the sensor sample under test.