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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.

The fatigue load spectrum of the physical proving ground is the necessary input for fatigue life analysis of vehicle parts and components. It is usually obtained by Road Load Data Acquisition (RLDA) and loads decomposition using multi-body dynamics tools. Virtual Proving Ground (VPG) methodology is gradually replacing this technical strategy. The belgian road is the typical event in durability test, in this paper, the flexible body and FTire model are applied to the vehicle multi-body dynamics model in order to improve the simulation accuracy. The result shows that all the wheel center force, shock absorber displacement and axial force acquired by VPG simulation have excellent correlation with real vehicle measured data. It is also proved that the virtual proving ground technology is a reliable and effective method to obtain the fatigue load spectrum in the early stage of development.

The underbody diffusers are used widely in race cars to improve the flow field structure at the bottom of the car and provide enough downforce. In recent years, passenger cars have begun to use bottom diffuser to improve aerodynamic characteristics, so as to reduce drag and increase downforce. In this paper, the aerodynamic characteristics of the bus with different underbody diffuser angles and channel numbers are studied by numerical simulation analysis. Firstly, the aerodynamics of the bus under different diffuser inlet and outlet angles are studied, and then an optimal inlet and outlet angle is determined based on the simulation results. Then, using this angle as a constant, the 2, 3, and 4 channel numbers were chosen as the diffuser channel variables to study the influence of the multiple-channel diffusers on the aerodynamic drag of the vehicle.

Battery state estimation is one of the most important decision parameters for lithium battery energy management. It plays an important role in improving battery energy utilization, ensuring battery safety and enhancing system reliability. This paper is proposed to provide a dynamic correction of SOC in the full working condition, including static condition and dynamic condition. Based on the Coulomb-counting method, the current SOC value of the battery is calculated. Under the static conditions, the open circuit voltage of the battery is used to directly collect the initial SOC. Under the dynamic working conditions, the open circuit voltage of the battery is estimated by the sliding mode observer. Based on the deviation between the calculated and estimated values of the open circuit voltage, the current coefficient of the Coulomb-counting method is dynamically corrected by PI strategy.

As automobiles are gradually transforming from independent mechanical units to network nodes with intelligent and networked functions, the functions and performance evaluation of intelligent vehicles is facing the new challenges. At present, China has initially classified the level of intelligent vehicles on the basis of SAE, but has not yet formed a scientific, rigorous and comprehensive evaluation system. Therefore, this paper proposes the detailed intelligent evaluation ideas of intelligent vehicles in different levels from 0 to 5 and sets up a "Trinity" evaluation system covering professional evaluation, practical evaluation and market evaluation. Then, with the development progress of intelligent vehicles, we will set up the hierarchical structure of evaluation indicators basing on automated intelligence and connected intelligence.

The two-wheeler is a vehicle that runs on two wheels, which is classified as motorcycle, electric-bicycle, and bicycle in this research. China has the largest number of two-wheelers and relevant accidents in the world. The two-wheeler riders have a high level of vulnerability, creating a significant necessity to better understand the characteristics according to the road-user group. The objective of this paper is to study the characteristics and analyze the causes of two-wheeler accidents in China using the CIDAS (China In-Depth Accident Study) Database. 2012 cases of two-wheeler accidents with riders injured or dead were collected from the CIDAS Database from 5 cities (Changchun, Beijing, Weihai, Ningbo and Foshan) in China over a period of 5 years (2011.07-2016.06).

The aim of the study was to investigate the difference between car-to-e-bikes and car-to-pedestrian accidents. The China In-depth Accident Study (CIDAS) database was searched from 2011 to 2013 for pedestrians and e-bikes struck by car, van and SUV fronts, which resulted in 104 pedestrian and 85 e-bike cases where information was sufficient for in-depth analysis. Reconstruction by PC-Crash was performed for all of the sampled cases. Pre-crash parameters were calculated by a MATLAB code. Focus was on prototypical accident scenarios and causes; speed as well as possible prevention countermeasures. It has been shown that traffic light violations, road priority violations, and unsure safety (these situations included misjudgments, unpreparedness, proximity to other road users, inappropriate speeds, etc.…) are the main causes in both the VRU groups. Distinctions were found for aspects of car collision speed, accident scenario, distribution of head contact points and so on.

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.