基于改进粒子群算法的ICPT系统多约束多参数优化

Multi-constraint multi-parameter optimization on efficiency of inductive coupling power transfer system based on improved particle swarm optimization

针对影响感应耦合电能传输系统传输功率和效率因素众多,造成系统参数设计困难,效率优化计算复杂的问题,首先介绍ICPT系统设计模型及参数约束条件;接着,基于一种改进的求解有等式约束优化问题的粒子群优化算法,在有等式约束优化算法的基础上,引入收缩因子和变异算子,有效地提高算法的收敛速度和精度;然后,针对一个特定输出功率的ICPT系统,通过优化系统互感耦合系数、谐振频率、负载电阻等多个参数,最大限度地提高系统的效率;最后搭建仿真实验平台,对不同参数组合模式下的系统传输功率和效率进行比较分析,仿真结果验证了算法的有效性。

To aim at the problem that there are many factors affecting the transmit power and efficiency of the ICPT system, which made the parameter design of system too difficult and the optimization calculation for its efficiency too complex, the design model and the parameters constraints of ICPT system are introduced firstly. Then, based on an improved swarm optimization algorithm used to solve the equation constrained optimization problem, the equa- tion constrained optimization algorithm with introduction of the shrinkage factor and the mutation operator effectively improved the convergence speed and accuracy. Next, to aim at a given output power ICPT system, system efficien-cy was improved at most by means of optimizing the system mutual inductance coupling coefficient, resonance fre- quency, load resistance and other parameters. Finally, simulation and experimental platform is built for comparing and analyzing transmission power and efficiency of systems with combination of different parameters, and the nu-merical results and the experiment results verified the effectiveness of the algorithm.