The battery pack, as the power source for new energy vehicles, is one of the most important components. The battery shell not only plays a vital role in protecting the battery package, but also contributes significantly to the vehicle's lightweight design, accounting for 2% to 6% of the total weight of the vehicle. Based on the global automotive industry's development goals for energy conservation and emission reduction, this paper discusses the development status quo of the new energy vehicle battery case industry, focusing on three aspects of safety, lightweighting and reliability. The common key technical challenges in this field are discussed, and the future development trends are proposed.

Road surface unevenness significantly affects both the driving safety of road vehicles and their dynamic responses. However, the existing datadriven methods for road surface classification struggle to efficiently handle timevarying parameters and vehicle speeds. Meanwhile, the existing modelbased road surface recognition algorithms require known and accurate vehicle models, facing the challenge of acquiring vehicle physical parameters in realworld applications. This paper proposes a novel pavement classification algorithm that begins by backcalculating the equivalent pavement profile, followed by data preprocessing. Subsequently, it computes time and frequency domain features for the equivalent pavement profile and response information, and key features are extracted using the ReliefF algorithm. A radial basis function neural network is used to construct a classifier for pavement grading and recognition. Finally, the robustness of the proposed algorithm is verified through simulation tests and realvehicle tests with different vehicle parameters and speeds.

The hollow roof spoiler has become a new trend in automotive styling design, significantly impacting the vehicle's aerodynamic performance. To study the influence of the spoiler parameters on aerodynamic drag coefficient, CFD simulations were conducted to analyze cases with different spoiler angles, passage sizes, and Dpillar spoilers based on a BYD hatchback model with a hollow roof spoiler. The simulation results agree well with wind tunnel experiment results. It is found that the volume of the upper tail flow increases with a decrease in the spoiler angle, a reduction in the passage size or the addition of a Dpillar spoiler. A lower drag coefficient is obtained when the upper tail flow more effectively matches with the lower tail flow. The findings of this paper are valuable for guiding future designs of hollow roof spoilers.

To quantitatively evaluate the environmental benefits of the recycling process for new energy vehicle power batteries, and to provide support for the improvement of the management system and relevant standards for endoflife power batteries, thereby assisting in the implementation of the national “twocarbon" goal, the paper selects ternary lithium batteries as the research subject. The paper identifies typical scenarios for power battery recycling and utilization, divides the lifecycle of ternary lithium batteries into four stages: raw materials acquisition, manufacturing and assembly, usage, and scrap recovery and establishes the corresponding GaBi model. Based on different recycling methods, such as wet recycling A, wet recycling B, and firewet combined recovery, a life cycle evaluation model for ternary lithium batteries was built and the carbon reduction efficiency of the recycling and reuse process was calculated. The research results show that the recycling of ternary lithium batteries significantly reduces carbon reductions. Specifically, the carbon dioxide emission reductions for each recycling method are as follows: 60.71 kg CO2/kWh for wet recycling A, 150.00 kg CO2/kWh for wet recycling B, and 153.57 kg CO2/kWh for firewet combined recycling. The carbon dioxide emission reduction efficiency of the three different recovery processes is ranked from best to worst as follows: firewet combined recovery, wet recovery B and wet recovery A. Proper recycling of power batteries can significantly reduce carbon emissions during the recycling process, thus producing greater environmental benefits.

Due to factors that the wiper swing frequency does not match the structure of the waterguiding channel and the air conditioning (AC) external circulation inlet, some vehicle models under rainy conditions experience water droplets or even water flow entering the AC system through the inlet, leading to the unpleasant odors from the air conditioning, and even water leakage into the passenger compartment, causing serious perceived quality issues. By employing the SPH method considering wiper movement, body posture, and the effects of airflow conditions, the paper uses PreonLab software to simulate a vehicle in rainy scenarios to address the water management issues. By adding a baffle at the position of the AC external circulation inlet, the entry of the rainwater into the AC system is significantly reduced, and this solution is verified through the real vehicle tests under rainy conditions. The proposed method can find and rectify the unreasonable flow path designs for vehicles in the rainy scenarios during the development stage without relying on real vehicle tests. The method can also be applied to other performance quality control of vehicle water management, such as wading and rain pollution.

To achieve multiobjective optimization of power performance and stability for inwheelmotor driven offroad vehicles in complex environments with variable adhesion conditions and undulating road surfaces, the paper proposed an adaptive torque control strategy based on pavement impact factors. Five characteristic parameters, namely, the difference in rolling resistance, normalized proportion of air resistance, normalized proportion of ramp resistance, variance of road adhesion difference and the minimum road adhesion coefficient, were used as inputs to establish a fiveparameter identification model of pavement impact factors based on fuzzy theory. Considering the identified pavement impact factors, an adaptive torque control strategy was developed for the multiobjective optimization of vehicle power performance and stability, and a threelayer control architecture was constructed. At the top of the strategy, the pavement impact factors are introduced to determine the urgency of acceleration, and the model predictive control algorithm is used to obtain the desired total driving force. The middle layer serves as the target decisionmaking layer, which governs the antiskid torque based on the optimal slip rate, and determines the desired feedforward compensation torque according to the road resistance. The base layer servers as the torque distribution level, taking the total demand driving force and the tire utilization ratio as the control objectives. It introduces the pavement impact factors to optimize the weight coefficients of these two objectives. A hybrid optimization algorithm with multiple constraints is applied for adaptive torque control. Simulations were conducted using the Matlab/SimulinkCarSim cosimulation platform, with real vehicle trials for verification. The results show that on lowadhesion road surfaces, the wheel slip control can be achieved rapidly within 0.2 s. On the split road surfaces, the lateral displacement is nearly negligible, showing excellent lateral stability. On highly twisted road surfaces, the system prevents large slip rates of the freespinning wheel from exceeding 0.2.

As the first pure electric sedan of BYD TOYOTA EV Technology Co., Ltd, the bZ3 has extremely high energy consumption requirements, which brings great challenges to its aerodynamic development. To achieve this target, CFD simulations and wind tunnel tests were conducted by the aerodynamics team. Optimizations were primarily focused on areas including styling, undercover design, cooling air inlet management, wheels and sealing. The final production car was tested in the wind tunnel, achieving a drag coefficient of 0.218, which is at a leading level among vehicles in its class. Different CFD methods were compared with test results, showing that the LBM has better accuracy, although its precision in simulating underbody airflow still needs to be improved.

Simultaneous localization and mapping (SLAM) technology enables autonomous vehicles to estimate their own poses and establish the map of an unknown environment according to the data collected by onboard sensors. SLAM can provide localization information to the decisionmaking module for vehicle planning, and has become one of the research hotspots of autonomous driving technology in recent years. Based on the point cloud data collected by LiDAR, this paper focuses on the SLAM technology applied in autonomous driving. The related research at home and abroad has been reviewed including the frontend odometry, the backend optimization and loop closure detection. Due to the limitations of a single sensor, the opportunities and challenges of multisensor fusion SLAM technology for autonomous driving are discussed based on the research hotspots and difficulties in the field of multisensor fusion.

Optimizing the aerodynamic performance of the vehicle chassis has an important impact on reducing the aerodynamic drag and lift of the vehicle. The optimized design in the chassis area is a crucial approach to improve the fuel economy and power of the vehicle. In this paper, a Computational Fluid Dynamics (CFD) simulation analysis of the external flow field is conducted for a sport utility vehicle (SUV). The paper compares the simulation accuracy of Realizable kɛ and SST kw turbulence models, ultimately selecting the Realizable kɛ turbulence model for the aerodynamic design of the chassis. Combining the SUV chassis characteristics and the flow field analysis, and aiming to minimize the overall cost, the paper designed five aerodynamic proposals for the chassis, including the front lower spoiler, the front wheel baffle, the subframe rear spoiler, the middle chassis guard and the tail muffler shape optimization. A fullscale wind tunnel test was carried out to verify the CFD simulation results. The results show that all five chassis proposals contribute to the improved aerodynamic performance. The tail muffler shape optimization has a notable impact on drag reduction, decreasing the vehicle's drag coefficient by 2.99%. When the five proposals are combined, the drag coefficient and lift coefficient are reduced by 5.16% and 21%, respectively. The study effectively achieves energysaving and drag reduction, and improves driving stability of the vehicle.

With the continued expansion of the pure electric vehicle market, it is necessary to optimize the overall thermal management control strategy for BEVs in low temperatures. The optimization is crucial to better suit the application scenarios, particularly to meet the growing demands of customers in northern cold regions and to alleviate the decline in driving range of BEVs in lowtemperature environments. Based on research and realvehicle validation of the thermal management control strategies for waste heat source heat pumps and air source heat pumps in different lowtemperature scenarios for a BEV model, the paper has extended the effective operating lower temperature limit of the heat pumpbased thermal management system from 15 °C to 20 °C. Moreover, the attenuation rate of driving range has been significantly reduced to 31.2% under the CLTC driving condition at 7 °C.