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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.

Gear rattle noise is one of the important characteristics of manual and dual-clutch transmission，it is generated by the impact of unloaded meshing gear pairs in the transmission due to engine torsional vibration. Based on a front-drive manual transmission and a five dynos drivetrain NVH test bench with high-speed sine wave generator function, this paper designs an experimental program suitable for transmission rattle noise. By driving dynamometer to simulate the torque fluctuation of real engine, the main research is to study the characteristics of the transmission rattle noise under different excitation amplitudes and different excitation frequencies, and the sensitivity of rattle noise under different gears, different oil temperatures, different excitation amplitudes and excitation frequencies is analyzed. Finally, the transmission maps of rattle noise in different gears can be obtained.

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.

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.

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.

With the advantages of flexible size and high energy density etc., pouch-type lithium ion battery cells with large capacity have been found more and more applications in electric vehicles. For these large-scale battery cells, thermal uniformity is vital for their safety and cycle life. To be specific, temperature gradients are expected to cause different degradation rates of active materials in different areas, which is possible to cause early failure or even fire and explosion of the battery cell. Thus, it is necessary to illustrate the batterie’s thermal uniformity in detail under different operating conditions. This work investigated the thermal uniformity of two 36 Ah pouch-type NCM/C battery cells with different sizes using both the thermal imaging method and thermoelectric effect method with K-type thermocouples. Experimental results show that there is an obvious temperature gradient on the surface of the pouch-type battery cell.

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.

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.

With the development of vehicle technologies, vehicle safety is much better than before, many companies put research focus on harder accident scenarios. The 25% overlapping collision is considered as one type of most dangerous collision, this paper study this type accidents base on CIDAS database. Paper showed 7 scenarios appeared frequency in China, 11, 12, 1 o’clock are main impact direction. High way and freeway are the main places, and the head, thorax and lower extremities were the main sites of injury.

To determine the vehicle chassis requirements, wheel force transducer (WFT) have been the best option when it is being used in targeting customer correlation or determining the effective use of the proving ground. However, using wheel force transducer in customer correlation fleet test is often unfeasible due to the huge cost and low practicability. As a result, engineers have to choose other transducer measures. This paper describes an effective approach of wheel force prediction by using the frequency response function (FRF) model of vehicle dynamic system. A vehicle system linear modelling technique is used. For the system identification of FRF, the acceleration and wheel force time history data, as system input and output, are collected from an instrumented passenger car as it traverses in different real-world proving ground surfaces. The obtained FRF represents the complex suspension mechanical model. Once the FRF is calculated, the predicted force signal can be implemented.

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.