The weighting coefficient matrix in the Linear Quadratic Regulator (LQR) of the active suspension system for vehicles has drawbacks of subjectivity and low efficiency. To address this issue, the paper proposes a weight coefficient matrix strategy based on the Red-billed Blue Magpie optimization algorithm. A 1/4 vehicle model, random road surface and impact road surface model are established. A linear quadratic regulator is designed, and a fitness function is constructed. The optimal weighting coefficient matrix and the minimum fitness function value are obtained through the Red-billed Blue Magpie algorithm in the search space. MATLAB/Simulink is used for simulation and a comparative analysis is conducted on passive suspension systems and active suspension systems under C-class road and impact road excitations, along with other optimization algorithms. The simulation results indicate that this proposed control strategy achieves optimizations of 75.50% for the vehicle body vertical acceleration, 48.23% for the wheel dynamic load and 47.63% for the suspension dynamic travel on Class-C road surface compared with the passive suspension and snake algorithm optimization active suspension control. The first peak value of vertical acceleration on the impact road surface is optimized by 76.80%, enhancing vehicle ride comfort and safety.

A vertical dynamic hybrid control method based on fuzzy inference rules and canopy damping control is proposed to meet the optimization requirements of multi condition control in vehicle dynamics. By constructing a closed-loop adjustment system with parameter dynamic adjustment mechanism and adaptive matching of system characteristics, a nonlinear mapping relationship between fuzzy membership function and canopy damping coefficient is established to achieve dynamic adjustment of canopy damping coefficient under different operating conditions. The simulation results show that compared with traditional ceiling control methods, this strategy significantly reduces the vehicle's heavy impact load.

In response to the problem of roll instability of a certain type of sedan under high-speed emergency steering conditions, the paper designed anti-roll control models based on Proportional-Integral-Derivative (PID) control and Sliding Mode Control (SMC) using the vehicle dynamics simulation software CarSim. The controllers generate anti-roll moments through active suspension forces and distribute the anti-roll moments between the front and rear axles according to the vehicle's center of mass position. At the same time, a co-simulation platform based on CarSim and Simulink is established to compare and analyze key indicators such as vehicle roll angle, the relationship curve between roll angle and lateral acceleration, and the Lateral Load Transfer Ratio (LTR) under three typical working conditions: double lane change, steering step input and steady-state cornering. The results show that the vehicle can still maintain good roll stability during high-speed sharp turns under the control of anti-roll moments. In addition, considering the current trend of active suspensions/stabilizer bars towards high actuation forces, the influence of counter-roll moments on vehicle roll stability was analyzed. The study found that compared to anti-roll control, counter-roll control can not only significantly reduce the vehicle's LTR but also effectively change the vehicle's roll-steer characteristics.

To address the stability challenges faced by four-wheel independent drive electric vehicles with hub motors under high-speed conditions, this study designs a non-singular adaptive sliding mode control architecture. The process begins by establishing a vehicle dynamics model, followed by designing a non-singular coefficient-type integral terminal sliding surface. An adaptive law is introduced to compensate for system uncertainties and external disturbances. The upper controller determines the required additional yaw moment based on stability boundaries to assess the vehicle's dynamic stability in real time. The lower controller aims to minimize road adhesion consumption and allocates the additional yaw moment to the four driving wheels via a torque distribution controller. Simulation studies based on the MATLAB/Simulink-CarSim platform under double-lane change and sinusoidal steering conditions demonstrate that, the proposed strategy exhibits smaller deviations in key performance aspects with yaw rate and sideslip angle as evaluation metrics. This not only indicates superior control effectiveness and robustness under external disturbances but also confirms its capability to meet the high-standard ride comfort control requirements of four-wheel independent drive autonomous vehicles.

To address the issue of response hysteresis in electronically controlled dampers caused by the static friction of electromagnetic valves, a dynamic response time model of the electronically controlled damper is established by combining the principles of Pulse Width Modulation (PWM) and dithering control. Through the construction of an electromagnetic valve test system for electronically controlled dampers, the influence of the amplitude and frequency of the dithering signal on the dynamic response of the electronically controlled damper is investigated. The precise control of PWM+dithering, data acquisition of current and force, and automatic calculation of dynamic response time are realized. The experimental results show that appropriate dithering amplitude and frequency can effectively improve the dynamic response performance of the electronically controlled damper, shorten the response time, and there exists an optimal parameter combination that minimizes the dynamic response time.

To enhance the damping characteristics of the dampers to better meet practical demands, this paper conducts an optimization analysis on the damping structural parameters. With an electromagnetic valve-type damper as research object, this paper analyzes its structure and working principle. Based on the mechanism of damping force generation, a damper simulation model is established in AMESim and compared with the bench test results, verifying the accuracy of the model. Utilizing the DOE module in AMESim, the influence degree of structural parameters on damping force is obtained, and the parameters that have a greater impact on the damping force are selected. Using the optimization module, the structural parameters are optimized with the target damping force curve as the goal. Simulation results show that compared to that before optimization, the maximum recoverable damping force increases by 34.61%, while the maximum compression damping force increases by 9.67%. The optimized damping characteristic curve is closer to the target curve, making it easier to meet the actual engineering requirements through parameter optimization.

The rolling resistance test at low temperature and normal temperature is conducted with 20 tire samples. This article analyzes the increase amplitude of low temperature rolling resistance coefficient, and it is shown that tire rolling resistance coefficient shows a remarkable increase trend at low temperature environment. The article takes a battery electric SUV as the research objective to analyze the impact of low-temperature rolling resistance on vehicle driving resistance through tire RR test data. A China Light duty vehicle Test Cycle-Passenger (CLTC-P) energy consumption simulation model is established based on AVL Cruise software to analyze the impact of low-temperature tire rolling resistance on drive energy consumption through simulation. Low-temperature and normal temperature energy consumption test of this SUV is conducted, comparison and verification of test energy consumption and simulation energy consumption are completed. The results indicate that vehicle 100 km drive energy consumption in low temperature environment increases by 4 kW·h, the rise of low temperature tire roll resistance increases 100 km drive energy consumption by 2.3 kW·h.