To extend the range of rear-drive electric buses, a brake force distribution control strategy based on intention recognition is proposed. Firstly, 400 sets of real-vehicle braking data were collected and analyzed. The brake pedal opening and its rate of change were used to calculate the braking force applied to the front and rear axles. Considering the battery constraints and the regenerative braking constraints of the rear axle motor, the braking control strategy is formulated and validated using Simulink-Trucksim joint simulation. The results show that the composite braking control strategy based on intention recognition achieves an accuracy of 95.7% in detecting the driver's braking intention. Under typical urban driving cycle in China, the fuzzy neural network-based energy recovery strategy, the fuzzy control recovery strategy, and the conventional recovery strategy increased the final state of charge (SOC) by 2.69%, 2.09% and 1.83%, respectively, compared with the non-recovery control strategy.

The slide movement pattern of traditional mechanical presses is relatively fixed, and quasi-static stamping simulations usually ignore the effect of strain rate. In contrast, servo presses feature a flexible slide stroke and adjustable stamping speed; thus, a material constitutive model that includes the strain rate effect is necessary to achieve accurate servo stamping simulations. To address the limitation of obtaining the stress-strain curves at only a finite number of strain rates through tensile tests, this paper analyzed and evaluated the strain rate-sensitive models, including the power law model, linear power law model, Johnson-Cook model and Cowper-Symonds model, using DDQ steel test data for model fitting as an example. Curve fitting is performed for segmented strain range and grouped strain rates, the parameter identification methods in each model are constructed and the applicability of each model in finite element software is discussed. The results provide guidance for selecting an appropriate constitutive model for servo stamping simulations.

This paper discusses the challenges of applying virtual reality (VR) in visual simulation and real-time rendering for automotive research and development. Focusing on the application scenarios and practical needs of automotive virtual development, a high-performance VR computing system based on real-time ray tracing and parallel rendering has been established for the first time among domestic automotive companies. By using the Bounding Volume Hierarchy (BVH) acceleration structure while optimizing algorithm parameters and network configuration, high-precision real-time visualization of large-scale vehicle models has been achieved. The offline rendering process, which previously took several hours, has been optimized to real-time rendering in just 1～2 seconds. The system effectively simulates ambient light refraction and reflection on parts, light uniformity and leakage, and physical occlusion between parts. Compared with traditional rasterization rendering, this approach has made a significant breakthrough, achieving over 90% physical realism. Through full-process implementation in several vehicle projects, it has replaced many physical models and reduced sample costs in the R&D process.

The paper examines the door sealing cavities near the B-pillar, C-pillar and the top of the tailgate of a SUV. The geometric features of these cavities are extracted and represented using three equivalent regular cavity models. The experimental studies on the sound phenomena and formation mechanism of these cavities were carried out in a small acoustic wind tunnel. The results indicate that the three cavities exhibit two different sound phenomena, i.e. strong resonance and weak resonance. Further numerical simulations are performed to analyze the acoustic characteristics of the cavities. The results show that self-excited oscillations are difficult to form in the small opening cavities, such as those near the B-pillar and C-pillar. Instead, pulsating excitation at the opening induces weak resonance in the cavity mode. In contrast, the cavities with wider openings near the tailgate can form self-excited oscillations, which resonate with cavity acoustic modes or Helmholtz resonance modes to produce strong resonance with whistling noise. The differences in phenomena and mechanisms between automobile door sealed cavities and large cavities are revealed. A method for determining the frequency of self-excited oscillations is proposed by characterizing the vortex motion in the Q-factor cloud diagram. Additionally, the contribution of self-excited oscillations to the peak values in the cavity sound pressure spectrum is clearly explained, while effectively defining their frequency.

The rapid development of new energy vehicles has dramatically increased the demand for battery materials such as lithium, cobalt, nickel, and manganese. To assess the supply risks of these resources, the demand for battery materials in China's new energy passenger vehicles from 2023 to 2050 was predicted using the Gompertz curve model and material flow analysis, under two different scenarios of battery technology development. The results indicate that by 2050, under the lithium iron phosphate route (LFPR), the demand for lithium, cobalt, nickel, and manganese will be 238, 169, 362, 158 kilotons, respectively. Under the nickel-manganese-cobalt (NMC) lithium battery route, the estimated demands will reach 242, 201, 1 084, 187 kilotons, respectively. Recycled lithium, cobalt and nickel in 2050 are expected to meet at least 86.5%, 93.5% and 65.8% of their annual demand, respectively. Given the current lack of comprehensive laws and regulations for waste battery recycling in China, it is essential to develop relevant standards.

To enhance the thermal safety of lithium-ion battery packs, this paper proposes a liquid-cooled thermal management structure with bionic channels resembling leaf veins. The thermal performance of the model is analyzed and optimized using the fluid dynamics software STAR-CCM+. Using the polar-variance method in orthogonal testing, the effects of multi-parameter coupling, including the number of cooling plate channels N, the channel width W, and the inlet flow rate Q, on key factors such as the maximum battery temperature T_max, the average temperature T_avg, the surface temperature difference ΔT, and the cooling hydraulic pressure drop Δp are investigated. The results show that N and Q are the primary factors affecting cooling performance, with W being a secondary factor. The optimal overall performance of the cooling plate is achieved at N=12, W=8 mm, and Q=25 g/s. After optimization, the leaf-vein-like cooling plate shows a 1.32% reduction in T_max, a 0.64% reduction in T_avg, and an 88.2% reduction in Δp compared to the S-type channel cooling plate.

Based on the experimental validation of a single-cell heat generation model, this paper proposes a thermal management battery module for a liquid-cooled system integrated with phase change material (PCM). The effects of the number of cooling channels, flow rate, cold channel arrangement and cooling plate thickness on the maximum temperature and temperature uniformity of the battery pack are quantitatively studied by using numerical simulation methods. The results show that at the discharge rate of 4 C and 35 ℃, altering the coolant flow rate in three cooling channels can greatly affect the maximum temperature and the maximum temperature difference of the battery module. Furthermore, once the coolant flow rate exceeds 0.2 m/s, the heat dissipation performance of the battery module does not show significant improvement. With the same number of cooling channels, the best temperature uniformity between battery packs and along the axial direction is achieved with a staggered distribution of coolant inlets and outlets. When the cooling flow rate and the number of cooling channels remain constant, increasing the thickness of the cooling plate can reduce both the maximum and minimum temperatures of the battery module. However, once the thickness reaches 8 mm with three cooling channels, further changes in temperature become negligible.

This article analyzes the structural characteristics and operating principles of a two-stage piston hydrogen pressure reducer with constant output. Based on the principles of statics and aerodynamics, a theoretical calculation model is established to examine the pressure output characteristics and flow properties of this pressure reducer. Theoretically, it has been proven that a two-stage structure pressure reducer provides more stable output pressure than a single-stage pressure reducer. Due to the extremely small size of hydrogen molecules, they are prone to leakage, making dynamic sealing between the piston and the housing very challenging. This article proposes a design strategy to replace dynamic sealing with static sealing, providing guidance for the development of high-pressure hydrogen pressure reducers.

To address the issue of high energy consumption in battery electric buses at signalized intersections, this paper proposes an eco-driving optimization model based on the Twin Delayed Deep Deterministic (TD3) policy gradient algorithm. First, a simulation training platform is developed using SUMO, which balances energy consumption, travel efficiency, comfort, and safety in a multi-objective optimized reinforcement learning reward function. Next, an eco-driving optimization model is created within the TD3 framework, tailored to the operational characteristics of electric buses at signalized intersections, and its parameters are trained. Finally, the performance of the proposed model is validated against the classic intersection passage strategy, Green Light Optimal Speed Advisory (GLOSA). The results show that the proposed eco-driving strategy reduces energy consumption by 9.82%, 26.13%， 19.00% and 14.51% in four typical intersection scenarios, while also maintaining vehicle safety, comfort, and travel efficiency.

To reduce the impact on the vehicle and minimize brake force fluctuations during mode transitions in the electro-hydraulic composite braking system, a control strategy for electro-hydraulic composite braking has been proposed, focusing on dual-motor driven electric vehicles with both front and rear wheel drive. This strategy includes a wheel cylinder pressure following control approach and a motor compensation control approach. The wheel cylinder pressure control, activated during hydraulic brake intervention, utilizes H_{\mathrm{\infty }} robust control to enable the hydraulic braking system to swiftly and precisely manage the magnitude of braking force. As a result, the braking system is stabilized, ensuring reliable vehicle control. To enhance braking comfort, a fuzzy PID-based motor compensation control strategy is employed during the intervention or withdrawal of hydraulic and regenerative brakes. This strategy reduces the impact on the composite braking system caused by variations in system response. The simulation conducted on the Simulink-AMESim-CarSim platform has verified that the hydraulic braking system can rapidly and accurately follow the target braking force. Furthermore, the results show that compared to an uncontrolled situation, the fluctuation in braking force is reduced by 90% and the shock is reduced by 74%, thereby significantly improving braking smoothness.