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The rapid advancement of new energy vehicle technology has led to the widespread placement of battery packs at the bottom of vehicles. However, there is a lack of corresponding regulations and standards to guide aspects related to vehicle bottom safety. This lack of guidance obscures the relative importance of various parameters impacting the structural safety of battery packs under dynamic impact conditions. Consequently, research on battery pack bottom collisions holds practical significance and offers valuable reference material. This study proposed a method based on the first collision point to examine the impact of bottom collisions on the mechanical safety performance of battery pack bottoms. A finite element model of the battery pack was established to investigate the effects of different impact types.

The China Automotive Technology and Research Center (CATARC) has completed two new wind tunnels at its test centre in Tianjin, China: an aerodynamic/aeroacoustic wind tunnel (AAWT), and a climatic wind tunnel (CWT). The AAWT incorporates design features to provide both a very low fan power requirement and a very low background noise putting it amongst the quietest in the automotive world. These features are also combined with high flow quality, a full boundary layer control system with a 5-belt rolling road, an automated traversing system, and a complete acoustic measurement system including a 3-sided microphone array. The CWT, located in the same building as the AAWT, has a flexible nozzle to deliver 250 km/h with an 8.25 m2 nozzle, and 130 km/h with a 13.2 m2 nozzle. The temperature range of the CWT is -40 °C to +60 °C with a controlled humidity range of 5% to 95%. Additional integrated systems include a variable angle solar simulator array, and a rain and snow spray system.

With the continuous development of the electrical vehicles (EVs), the electric power network and transportation network are interconnected by EVs which require a coordinated operation of the two networks. In view of these coupled networks, this paper proposes a charging navigation strategy for EVs based on charging power adjustment, which can not only provide the navigation path with the shortest total operational time for EVs from the origin node to the completion of charging, but also effectively reduce load fluctuations in the electric power system. In the electric power system, an innovative optimization strategy for adjusting the EV charging power distribution is proposed, which can adjust the charging power in a timely and effective manner according to the response of EV charging. The multi-objective particle swarm optimization (MOPSO) algorithm and the improved Dijkstra algorithm are used for solving the obtained the EV charging power adjustment plan and charging paths.

The automotive active infrared detection system is usually applied to the night driver assistance system or the diver attention monitoring system. However, the infrared light emitted by the active infrared detection system can cause damage to retina, cornea and eye crystals. This paper has studied the photobiological safety of the infrared light source used in the automotive active infrared detection system. Although it has been already have the general requirements of photobiological safety in international standards, there is not any requirements for automotive active infrared detection system. The range of the active infrared detection system depends on the radiation intensity of the infrared light source, but too much radiation intensity will cause harm to retina, cornea and eye lens when the infrared light source is too close to eyes.

Fuel cell reactors, as the core components of fuel cell vehicles, have a short life problem that has always limited the development of fuel cell vehicles. The life attenuation curve of fuel cell shows nonlinear characteristics, and there is no model that can accurately predict its effect. This paper is based on the experimental data of the vehicle fuel cell reactor, which is derived from the 600 h durability test run by a 4 kW fuel cell reactor. The relevance vector machine, as a Bayes processing method that supports vector machine, is a data-driven method based on kernel functions. The regression model is established by the relevance vector machine, and the super-parameters are found by genetic algorithm, because the kernel function strongly affects the nonlinearity of the curve, and the decay curve of fuel cell reactor performance is predicted according to four different kernel functions.

In this study, a new system of assessment method was developed to evaluate the characteristics of urban buses based on remote online monitoring. Four types of buses, including China V emission standards diesel bus, lean-burn CNG bus, air-fuel equivalence ratio combustion CNG bus and gas-electric hybrid bus, were chosen as samples to analyze the emission characteristics of urban buses with different engine types in urban scenario. Based on the traffic conditions in Beijing, the actual emission characteristics of buses under newly-built driving conditions were analyzed. Moreover, the emission factor database of urban buses in Beijing was established to analyze the characteristics of excess emission. The research results are shown as follows. 1) Compared with other types of buses, NOX emission factor and emission rate of lean-burn CNG bus are much higher.

An appropriate energy management strategy can further reduce the fuel consumption of P2 hybrid electric vehicles (HEV) with simple hybrid configuration and low cost. The rule-based real-time energy management strategy dominates the energy management strategies utilized in commercial HEVs, due to its robustness and low computational loads. However, its performance is sensitive to the setting of parameters and control actions. To further improve the fuel economy of a P2 HEV, the energy management strategy of the HEV has been re-designed based on the globally optimal control theory. An optimization strategy model based on the longitudinal dynamics of the vehicle and Bellman’s dynamic programming algorithm was established in this research and an optimal power split in the dual power sources including an internal combustion engine (ICE) and an electric machine at a given driving cycle was used as a benchmark for the development of the rule-based energy management strategy.

Life prediction is a major focus for a commercial fuel cell stack, especially applied in fuel cell electric vehicles (FCEV). This paper proposes a data driven fuel cell lifetime prediction model using particle swarm optimized back-propagation neural network (PSO-BPNN). For the prediction model PSO-BP, PSO algorithm is used to determine the optimal hyper parameters of BP neural network. In this paper, total voltage of fuel cell stack is employed to represent the health index of fuel cell. Then the proposed prediction model is validated by the aging data from PEMFC stack in FCEV at the actual road condition. The experimental results indicate that PSO-BP model can predict the voltage degradation of PEMFC stack at actual road condition precisely and has a higher prediction accuracy than BP model.

Due to the rapid development of road infrastructure and vehicle population in China, the fuel consumption and emission of on-road vehicles tested in China World Transient Vehicle Cycle (C-WTVC) cannot indicate the real driving results. But the test results in China Heavy-duty Commercial Vehicle Test Cycle-Coach (CHTC-C) based on the road driving conditions in China are closer to the actual driving data. In this paper, the model for predicting the performance of heavy-duty vehicles is established and validated. The fuel consumption and NOx emission of a Euro VI heavy-duty coach under C-WTVC and CHTC-C tests are calculated by employing the developed model. Furthermore, the fuel consumption of the test coach is optimized and its sensitivity to the driving factors is analyzed.

SOC (State of charge) plays an important role in vehicle energy management, utilization of battery pack capacity, battery protection. Model based SOC estimation algorithm is widely regarded as an efficient computing method, but battery model accuracy and measuring noise variance will greatly affect the estimation result. This paper proposed an adaptive mixed estimation algorithm. In the algorithm, the recursive least squares algorithm was used to identify the battery parameters online with a second-order equivalent circuit model, and an adaptive unscented Kalman method was applied to estimate battery SOC. In order to verify the effect of the proposed algorithm, the experimental data of a lithium battery pack was applied to build a simulation model. The results show that the proposed joint algorithm has higher estimation accuracy and minimum root mean square error than other three algorithms.

As one of the core components of electric vehicles(EV), the drive motor system has a significant impact on the EV operation performance. The interior permanent magnet synchronous motor (IPMSM) has a wide range of applications in EV, due to its high efficiency, high power density, high torque current and wide speed range. In the field of EV, motor control system is required to have a high operating range. IPMSM operates at constant torque mode below rated speed and constant power mode above rated speed. The back electromotive force(Back-EMF) generated by the rotor in the constant power mode causes the inverter output voltage to saturate. Therefore, it is necessary to ensure that the controller is still operating in the linear region by applying a flux weakening(FW) current to the stator.

The thermophysical parameters and amount of composite phase change materials (PCMs) have decisive influence on the thermal control effects of thermal management systems (TMSs). At the same time, the various thermophysical parameters of the composite PCM are interrelated. For example, increasing the thermal conductivity is bound to mean a decrease in the latent heat of phase change, so a balance needs to be achieved between these parameters. In this paper, a prismatic LiFePO4 battery cell cooled by composite PCM is comprehensively analyzed by changing the phase change temperature, thermal conductivity and amount of composite PCM. The influence of the composite PCM parameters on the cooling and temperature homogenization effect of the TMS is analyzed. which can give useful guide to the preparation of composite PCMs and design of the heat transfer enhancement methods for TMSs.

With the increasing frequency of fire incidents of electric vehicles, the safety of power batteries has attracted more and more attention. At present, the research on the safety of power batteries is mainly focused on fresh batteries. As the state of health of batteries deepens, how the safety of the battery evolves is not clear enough so far. This paper analyzes the external short-circuit safety of a NCM/C rectangular battery under different state of charges. The results show that when the cycle number is less than 800, the maximum temperature of the battery during short-circuit is below 130 °C. The main failure mode of the battery is bulging in volume or opening of the explosion-proof valve and there is no obvious regularity between the failure mode with the cycle life. However, when the cycle number reaches 1000, the battery goes into thermal runaway during the safety test.

Currently, there are no specific standards on electromagnetic compatibility (EMC) test for wireless charging system of electric vehicles (EVs). However, the EMC test items have been summarized in some international standards. And the national standard is under developing. In order to support the formulation of corresponding national standards and regulations, promote the rapid development of EVs industry and support the implementation of the national strategy of new energy vehicles (NEVs) and intelligent network vehicle, we carry out the EMC test for wireless charging systems. In this paper, the wireless charging system of EVs is taken as the research object, which can also been called equipment under test (EUT). Firstly, an introduction of the research status was summarized. And then, the influence parameters such as output power and offset are analyzed. Based on the analysis, the EMC test was implemented to evaluate the EMC performance of EUT.

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.

A control strategy for searching the optimal working interval based on multi-parameter logic threshold is proposed for the power system of distributed hybrid electric vehicles. The battery state of charge working area and boundary velocity threshold are combined with the optimal engine working curve. Offline simulation of 0-32 km/h acceleration performance is conducted. To further verify the validity of generating C code, a hardware-in-the-loop (HIL) test platform based on MATLAB/RTW/xPC target is built. Real-time simulation and real-time performance comparison test are performed. Test results show that the designed multi-parameter logic threshold control strategy achieves reasonable allocation of energy and improves the dynamic performance of vehicles. The xPC HIL simulation test system is feasible and provides a fast test verification method for vehicle control strategy development.

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.

Electric vehicles are considered as one of the most popular way to decrease the consumption of petroleum resources and reduce environmental pollutions. Motor control system is one of the most important part of electric vehicles. It includes power supply module, IGBT driver, digital signal processing (DSP) controller, protection adjustment module, and resolver to digital convertor. To implement the control strategies on motor control system, a lot of practical aspects need to be taken into accounts. It includes setup of the initial excitation current, consistency of current between motor and program code, over-modulation, field weakening control, current protection, and so on. In this paper, an induction motor control system for electric vehicles is developed based on DSP. The control strategy is based on the field-oriented control (FOC) and space vector pulse width modulation (SVPWM).

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.

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.