摘要
针对磁耦合谐振式无线电能传输(MCRWPT)系统在线圈过耦合时输出功率骤降的问题,提出了以粒子间方差衡量算法进程的自适应粒子群优化(APSO)算法.考虑频率分裂时系统功率和效率的特性,选定跟踪目标点为固有谐振频率右侧的最大功率点.所提的方差型APSO根据方差型算法进程因子动态调整参数,提高算法前期的全局性和后期的收敛性.仿真实验结果表明,所提的方差型APSO在实现MCRWPT系统的最大功率点跟踪时,稳态精度更高,收敛代数更少,算法的优势具有统计学意义.
To solve the problem that the output power of the magnetically coupled resonant wireless power transmission(MCRWPT)system drops sharply when the coils are over coupled,we propose an adaptive particle swarm optimization(APSO)algorithm that meassures the algorithm process by particle variance.Using frequency splitting to consider the power and efficiency characteristics of the system,the tracking target point is selected as the maximum power point on the right side of the inherent resonance frequency.The proposed variance APSO algorithm dynamically adjusts the parameters according to its variance process factor,which improves its global performance in the early stage and its convergence in the later stage.Simulations verifiy that the proposed variance APSO algorithm has higher steady-state accuracy and fewer convergence algebras when implementing the maximum power point tracking of the MCRWPT system,and the advantages of the algorithm are statistically significant.
作者
赵越
沈艳霞
ZHAO Yue;SHEN Yanxia(Engineering Research Center of Internet of Things Technology Applications Ministry of Education,Jiangnan University,Wuxi 214122,China)
出处
《信息与控制》
CSCD
北大核心
2021年第1期113-118,128,共7页
Information and Control
基金
国家自然科学基金资助项目(61573167,61572237)。
关键词
无线电能传输
频率分裂
最大功率点跟踪
粒子群优化(PSO)算法
wireless power transmission(WPT)
frequency splitting
maximum power point tracking
partical swarm optimization(PSO)
