## 4 Optimization of Adaptive Control Parameters for Permanent Magnet Synchronous Motors  
### Parameter Optimization System  
The improvement of motor performance requires continuous technical innovation and optimization of control parameters. In this paper, the adaptive control strategy of the permanent magnet synchronous motor is the main research object, and optimization research is carried out to improve the performance of the permanent magnet synchronous motor. In this paper, the Multi-objective Particle Swarm Optimization Algorithm and the Non-dominated Sorting Genetic Algorithm II are mainly used to enhance the robustness and stability of the permanent magnet synchronous motor. By integrating the Isight software (v.4.5) with Simulink (2023b), the optimization results of the desired objectives can be obtained easily and effectively. The main focus of this section is the establishment of the optimization system. The Isight software is a professional engineering analysis software for parameter optimization, design exploration, and model calibration. With Isight, we can define design variables, objective functions, and constraints to automate the search for optimal designs, thus saving time and resources. Its main advantage is the automated optimization process, which allows efficient optimization without manually adjusting parameters, as well as the global search capability, which allows us to search for the optimal solution in a large parameter space. At the same time, the Isight software supports a variety of optimization algorithms, such as genetic algorithms, particle swarm optimization, etc., which can be used to select the appropriate algorithm for optimization according to the specific problem. Building on its previously highlighted strengths, the Isight software also offers parallel computation, flexibility, and scalability in parameter optimization, enabling  
Figure 4: Block diagram of permanent magnet synchronous motor control using the STSM control method. fast and effective design optimization and improving the performance and quality of the product. In this paper, the Isight software is integrated with Simulink to achieve the desired optimization objectives. There are many factors affecting the performance of the motor, and in the adaptive control strategy proposed in Section 3 of this paper, we conclude through theoretical analysis that the sliding mode control parameters and the PID control parameters in the weak magnetic control of the MTPA have the most significant influence on the performance of the motor. In order to improve the stability and robustness of the motor, we determined that the sliding mode control parameters (\(K_{1}\) and \(K_{2}\)) in the STSM-MRAS and the PID control parameters (\(K_{\text{P}}\) and \(K_{\text{i}}\)), in the weak magnetic control of MTPA are the four design variables in this paper. Response output refers to the final output parameter of the optimization system, and it is also the index for evaluating the optimization process and results. In this paper, we select the response output as the peak speed and peak torque of the motor, and the optimization objective is to obtain the minimum response output at reasonable control parameters. In electric motor control systems, the reduction in torque overshoot significantly enhances system stability and facilitates smoother operational responses, thereby leading to improvements in overall performance and longevity. This aspect is especially crucial in new energy vehicles, wherein the torque generated by the motor directly influences the overall driving experience. Excessive torque overshoot may result in abrupt acceleration or deceleration, which adversely impacts driving comfort and safety. By minimizing torque overshoot, a more seamless and linear acceleration experience can be attained. Furthermore, the reduction in torque overshoot mitigates mechanical shocks, thereby prolonging the lifespan of critical components and reducing maintenance costs.