To solve the problem of the real-time path-planning of autonomous vehicles for obstacle avoidance on structured roads, a path-planning approach based on the B-spline algorithm is proposed in this paper. Firstly, the mechanism of driver path planning is analyzed, and a dynamic risk-identification model based on the support vector machine is proposed. It combines the driver’s risk perception characteristics and a risk model. Then, the B-spline algorithm model is improved based on the risk-identification model. Furthermore, road features, road constraints and dynamic constraints are considered to further optimize the planning algorithm. To verify the path-planning approach proposed in this paper, a co-simulation experiment based on CarSim/Simulink is conducted. Results show that the improved algorithm is effective in static and dynamic obstacles avoidance. The algorithm can generate collision-free obstacle avoidance paths, and the paths meet the real-time requirements and dynamic constraints of obstacle avoidance scenarios. In addition, the proposed algorithm optimizes the path according to the driver’s operating characteristics, which can further improve the safety and comfort of autonomous vehicles.

To meet the real-time path planning requirements of intelligent vehicles in dynamic traffic scenarios, a path planning and evaluation method is proposed in this paper. Firstly, based on the B-spline algorithm and four-stage lane-changing theory, an obstacle avoidance path planning algorithm framework is constructed. Then, to obtain the optimal real-time path, a comprehensive real-time path evaluation mechanism that includes path safety, smoothness, and comfort is established. Finally, to verify the proposed approach, co-simulation and real vehicle testing are conducted. In the dynamic obstacle avoidance scenario simulation, the lateral acceleration, yaw angle, yaw rate, and roll angle fluctuation ranges of the ego-vehicle are $\pm$2.39 m/s², $\pm$13.31°, $\pm$13.26°/s, and $\pm$0.938°, respectively. The results show that the proposed algorithm can generate real-time, available obstacle avoidance paths. And the proposed evaluation mechanism can find the optimal path for the current scenario.

The optimal design of a super highspeed flywheel rotor could improve flywheel battery energy density. The improvement of flywheel battery energy density could enhance the performance of the flywheel lithium battery composite energy storage system. However, there are still many problems in the structure, material and flywheel winding of super highspeed flywheels. Therefore, in this paper, electric flywheel energy and power density parameters are designed based on CPE (Continuous Power Energy) function and vehicle dynamics. Then, according to the design index requirements, the structure, size and material of the electric flywheel rotor are designed. Furthermore, the numerical analysis model of stress and displacement of multi-ring interference fit flywheel rotor under plane stress state is established. On this basis, the influence laws of flywheel rotor wheel flange numbers and interlaminar interference on stress distribution of flywheel rotor are analyzed, and the assembly form of wheel flange is determined. Finally, the stress check of the flywheel rotor is completed. The results show that the super highspeed flywheel rotor designed in this paper meets vehicle dynamics requirements in terms of energy storage and power. In terms of strength, it meets the design requirements of static assembly stress and dynamic stress at maximum speed.