单管感应电能传输系统参数全局优化

Global Optimization for Parameters in Single Switch Inductive Power Transmission System

针对单管感应电能传输系统参数优化中存在的设计参数约束少、参数非全局最优等问题,提出一种参数全局优化算法。将系统效率最高作为目标函数,以原副边电感、电容等关键器件的电压、电流大小为约束条件,将工作频率、原副边电感、电容作为优化变量,建立系统的非线性规划数学模型,采用智能优化算法进行模型解算。为避免算法收敛于局部最优,设计了"遗传算法+模式搜索"的混合算法,即在遗传算法求得最优解的基础上,采用模式搜索进行深度优化。仿真和实验结果表明,提出的方法能从全局角度对系统进行整体优化,单次优化得到所有最优参数,减少了工作量;求解时的混合优化算法具有较优的全局搜索能力,可用于其他约束优化问题。

A global optimization method is proposed to solve the problems such as less design parameter constraints and non-global optimal parameters in parameter optimization of single switch inductive power transmission system. The method can be divided into two steps. Firstly, a nonlinear programming mathematical model is established by taking the highest system efficiency as the objective function, the voltage and current scales of key devices such as inductor and capacitor in both sides as the constraint conditions, the working frequency, inductance and capacitance as the optimization variables. Secondly, an intelligent optimization algorithm is adopted to analyze the model. A hybrid optimization algorithm using genetic algorithm and pattern search is designed to avoid convergence to the local optimum, in which the genetic algorithm is used to obtain the optimal solution, then the pattern search is used for the further optimization. Experiment shows that the optimal parameters meet the actual requirements. The method can optimize the whole system from the global point of view, and once optimization can obtain all the optimum parameters to reduce the workload. The hybrid optimization algorithm with higher global search ability can also be applied to other constrained optimization problems.