Yong You

With the development of vehicle intelligence and electrification, the performance of vehicle chassis system is highly demanded. Most existing researches have adopted the structure parameters optimization design method for the partial chassis subsystem, which cannot improve global vehicle performance. In this paper, the chassis system of distributed drive electric vehicles is taken as the research object. The chassis system integration optimization design method is studied. Firstly, the dynamic vehicle model, which includes active suspension, electric power steering, and motor braking systems, is established. Secondly, according to the performance requirements of suspension, the riding comfort index is formulated. According to the requirements of steering performance, the indexes of steering road feel and steering sensitivity are derived. According to the performance requirements of the braking system, the braking feel index is formulated. Based on the subsystem indexes, the comprehensive performance evaluation index of “comfortable-stability” of electric vehicle chassis system is proposed for the first time. Aiming at the minimum of the weighted sum of each subsystem performance index, the optimization constraints of the suspension, steering, and braking systems are considered. In order to avoid the subjectivity of weight selection, the weight coefficient of the optimization target is determined by the weight method of CRITIC. Then the chassis system’s mathematical model of multi-objective optimization is established. Finally, based on the NSGA-II algorithm, the chassis system is optimized. And based on the simulation software, the comparative analysis is carried out. Simulation results indicate that compared with the unoptimized vehicle, the amplitude of FVA and RVA indexes of the optimized vehicle is reduced by 9.87% and 2.23%, the amplitude of steering road feel index is increased by 15.51%, and the amplitude of BF index is reduced by 20.13%. The comprehensive performance of the vehicle chassis has been improved.

As a critical component of electric vehicles, the powertrain has a significant impact on the overall performance of vehicles. In addressing the challenge of lengthy testing cycles, this study develops a para model of the powertrain, utilizing digital twin (DT) technology, thereby establishing a framework for simulation testing of multi-controller intermodulation. We establish functional definition coverage testing by designing specific functional requirement use cases, and we validate the failure mechanism via fault injection use cases. The results indicate that the DT testing platform can effectively simulate the operational interactions among various controllers within the powertrain system. In comparison to traditional field testing, the digital twin-based testing methodology offers enhanced operational efficiency and allows for the examination of testing conditions that are impractical to implement in real vehicles, particularly in the context of fault injection testing, thus facilitating the early detection of potential safety risks within the system. The advancement of this technical solution holds significant practical implications for the future mass production and development of electric vehicles.

Obtaining accurate motion state information is the foundation of active movement control systems and advanced driving assistance system. To accurately obtain vehicle motion state information without the high-accuracy dynamic models parameters, this paper proposes a vehicle state estimation algorithm based on Whale Optimization Algorithm-Support Vector Regression (WOA-SVR). A double-layer (longitudinal and lateral) regression estimation structure has been proposed based on analyzing the characteristic of vehicle dynamics. Then, the SVR model is trained on a dataset composed of multiple driving conditions, and the WOA is used to optimize the penalty factor c and kernel function parameter g in the relaxation variable during the training process; Finally, the estimation algorithm was validated through virtual simulation of single line change and frequency sweep tests, as well as ABS braking and double line change actual vehicle tests. The results show that this algorithm effectively improves estimation accuracy and is robust to changes in speed.

As a critical component of electric vehicles, the powertrain has a significant impact on the overall performance of the vehicle. In addressing the challenge of lengthy testing cycles, this study develops a para model of the powertrain utilizing digital twin (DT) technology, thereby establishing a framework for simulation testing of multi-controller intermodulation. The research conducts functional definition coverage testing through the design of specific functional requirement use cases, and it validates the failure mechanism via fault injection use cases. The results indicate that the DT testing platform can effectively simulate the operational interactions among various controllers within the powertrain system. In comparison to traditional field testing, the digital twin-based testing methodology offers enhanced operational efficiency and allows for the examination of testing conditions that are impractical to implement in real vehicles, particularly in the context of fault injection testing, thus facilitating the early detection of potential safety risks within the system. The advancement of this technical solution holds significant practical implications for the future mass production and development of electric vehicles.

The novel power-cycling variable transmission (PCVT) has special speed regulation characteristics, and its gearshift process is accompanied by sudden change of speed ratio and change of system efficiency, which affect the shift quality. In order to propose an effective shift control strategies, a dynamic model of shifting process is established based on the analysis of PCVT's working principle and speed regulation characteristics. According to the shifting mechanism of PCVT, the shifting process is divided into four stages, and the dynamic equation is established in stages. Based on the PCVT shift control requirements, the clutch and engine controller are designed in stages. For the torque phase, a finite time linear quadratic regulator is used to determine the optimal clutch engagement and disengagement speed, with the jerk and friction work as optimization indices. For the inertia phase, the fuzzy compensation controllers of the clutch and the engine are designed respectively under the comprehensive consideration of the factors such as the speed ratio of torque converter and the system efficiency. Simulation results show that the proposed shift control strategy can achieve smooth shift and meet the control requirements well.