Carbon Fiber Reinforced Plastic (CFRP) were used to replace traditional metals to construct battery pack box to achieve lightweight design of battery pack box. Firstly, based on performance requirements, finite element analysis was conducted for the dynamic and static performance of carbon fiber battery pack, topography and size optimization was carried out on the upper cover plate, and structural optimization was made on the lower box body respectively, which increased the first-order natural frequency to 50.63 Hz and reduced weight of the lower box by 31.1%. Secondly, optimization analysis was made on the box layer, and based on the Isight platform, multi-objective optimization was conducted on the weight and first-order natural frequency of the lower box, meanwhile the entropy TOPSIS decision-making method was used to determine the optimal layer design scheme. Finally, the layer sequence was optimized by considering the lamination board laying process. The optimization analysis results show that lower box achieves a weight reduction of 58.9%, and both the maximum displacement and maximum stress under all operating conditions were reduced, and the dynamic and static performance of the battery pack box has been improved.

In order to prevent vehicle mass changes and road slope interfering with longitudinal speed of autonomous driving truck, this article utilizes an intelligent navigation system to obtain information including vehicle speed trajectory and road slope. Vehicle longitudinal dynamic model and Compressed Natural Gas (CNG) engine dynamic model are established, and a real-time Dynamic Programming (DP) speed trajectory tracking controller is designed based on the Model Predictive Control (MPC) framework. The simulation results under NEDC and WLTC operating conditions show that the controller can keep vehicle speed stable under conditions of truck mass change and road slope interference, and can optimize speed tracking error while reducing natural gas consumption.

In order to meet the rapid response of the automobile brake-by-wire system to the control motor, this paper proposes an improved super-twisting sliding mode algorithm to realize the accurate control of the brake master cylinder pressure. The paper firstly analyzes the convergence and stability of classical super-twisting sliding mode algorithm, then proposes an improved strategy of super-twisting sliding mode algorithm to solve the problem of slow convergence at the position where the sliding surface is far from the equilibrium point. The stability of the proposed algorithm is proved by theoretical analysis of Lyapunov equation. Finally, the effectiveness of the algorithm is verified by simulation and bench test of brake-by-wire system. The results show that the improved super-twisting sliding mode algorithm improves the convergence speed of the pressure overshoot of the brake-by-wire system by 3.87%, and the steady-state error is controlled within 2%, which improves the control robustness and demonstrates good control performance.

In order to suppress the knocking phenomenon of hybrid engine, a Computational Fluid Dynamics (CFD) model is established based on the ultra-high compression ratio hybrid engine. Bench tests are carried out to analyze the influence of engine subsystem and control parameters on knocking. The results show that rapid combustion can be achieved by increasing the inlet tumble ratio. Improving the machining accuracy of the combustion chamber can improve the consistency of combustion. Separate cooling of cylinder block and cylinder head can realize intelligent temperature regulation. The addition of a water baffle can reduce the temperature of the metal. For the maximum effective thermal efficiency point of the engine, reducing the pressure loss of the Exhaust Gas Recirculation (EGR) system can make the EGR rate reach 25%. In high-temperature environments, the effective compression ratio and engine outlet temperature require precise control.

In order to predict the induction noise of commercial vehicles, a new 1-D simulation model of air compressor is proposed. The Compressor-Engine coupling simulation model can predict the frequency and amplitude of the noise at the main order accurately, and can both recognize the order noise from the air compressor and the engine in the meantime. The characteristic of compressor noise and the noise reduction method of compressor path are studied by this coupling model. The results show that the noise of the compressor has typical pulse noise characteristic. When dealing with this type of noise, the arrangement sequence of different types of mufflers will have a significant impact on the noise reduction effect.

To address the cracking issue of the rear rubber bushing in the front suspension lower control arm during road testing for a specific vehicle, a life simulation method considering the influence of the diameter shrinkage is proposed. Firstly, the static stiffness of the bushing after diameters shrinkage is simulated, and combined with multi-objective optimization, hyper elastic constitutive parameters that accurately describe the force-displacement characteristics of the bushing are obtained. Then, on the basis of considering pre-strain from diameter shrinkage, crack grow algorithm methods are employed to predict bushing life, achieving a damage level of 2.01 at critical location, which replicates the cracking problem observed in road tests. Finally, through structural optimization design, damage at hazardous locations is reduced to 0.943. The road test results show that the fatigue life of the optimized bushing can be improued effectively, and the proposed scheme is proved to be effective.

It is crucial to effectively identify abnormal connections in the battery system of new energy vehicles in order to address their operational safety issues. By utilizing an emergency warning cloud monitoring platform and big data analysis methods, combined with the similarities and differences in data patterns between normal vehicles and vehicles with abnormal or faulty connections, this paper aim. to explore the factors contributing to abnormal defects in power battery connections. A data-driven algorithm for identifying abnormal risk factors in the connection of new energy vehicle battery systems is developed. According to the risk factors, the degree of abnormal connection in the battery system is classified into different levels, and the results show that the proposed algorithm can accurately and effectively identify high-risk vehicles with abnormal connections.

In order to study the influence of shielding structure on electvical vehicles wireless charging system, based on the theory of shielding effectiveness, this paper establishes a relationship model between the thickness of the shielding material and its parameters. Firstly, the shielding effectiveness of single-layer shielding materials with different thicknesses and different shielding materials on the magnetic field is analyzed, and the numerical solutions are compared with the analytical solutions to preliminarily validate the accuracy of the established shielding material thickness model. Based on this, a composite wireless charging shielding structure with the minimum thickness is proposed under the premise of ensuring electromagnetic safety and verified by electromagnetic tests. The results show that when a combination of 0.05 mm ultra-thin silicon steel and 2.52 mm ferrite is used as a dual-layer shielding, the magnetic field intensity reaches the safety limit, and the transmission efficiency reaches 90.92%. Compared with the traditional ferrite and aluminum composite shielding structure, the thickness of the shielding structure is reduced by 1.95 mm.

In order to solve the problem of the robustness of the performance of automotive acoustic package parts in mass production, an uncertainty optimization method based on interval analysis is proposed. The BIOT theory and the transfer matrix method are used to simulate the sound absorption and insulation performance of the acoustic package parts, the Interval perturbation theory is used to analyze the uncertainty of acoustic performance, and the interval uncertainty optimization method is introduced to optimize the material selection and structural design parameters of the parts. The results show that the method is used to analyze and design the inner front wall parts of a certain model, the quality of the parts decreases by 12.8%, and the robustness of the system is greatly improved, and the maximum fluctuation of insertion loss decreases from 8 dB before optimization to 5 dB after optimization.