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中文摘要：
针对感应电能传输系统因互感变化引起传输功率与效率降低的问题，设计了一种复合谐振结构，并给出一种改进的遗传算法对该结构进行参数优化。在分析传统谐振网络拓扑的基础上，给出一种复合谐振网络以提高互感变化时的传输功率与效率特性。以传输功率和效率最大为目标，建立了该结构的非线性规划数学模型，采用非线性单纯体法和混沌初始化混合方法来产生优良的初始种群，对目标和约束进行二次归一化后，利用可行性规则选择优良个体，并采用混合变异提高算法的全局搜索能力。最终优化结果与实验表明，改进后的算法能较快地找到全局最优参数，且参数结果优良，在互感大范围变化时能保持较高的传输功率及效率。
英文摘要：
In view of the problem that the transmission power and efficiency decrease in the inductive power transfer （IPT） system when mutual inductance varies, a composite resonant network is proposed with a refined genetic algorithm for parameter optimization. Through analyzing the topology of a traditional resonant network, a composite resonant network is proposed to improve the transmission power and efficiency characteristics against wide mutual inductance variations. With the maximum transfer power and efficiency as the objective function, a nonlinear programming mathematical model is established. A mixed method of the nonlinear simplex method and the logistic model is considered to generate the fine initial population, and two time normalization is proposed to deal with the objective function and constraints. The feasibility rules are used to choose better individuals, and a mixed mutation is designed to improve the global searching capability. Final results and experiment show that the refined method can find the global optimum parameters quickly, which well meets the design requirements with good transmission power and efficiency characteristic when mutual inductance changes in a large scale.
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