Abstract
In order to solve the problem of particle dilution in traditional particle filter (PF) estimation of Ni-Cd Alkaline battery state of charge (SOC), a bat algorithm optimized particle filter was proposed to estimate SOC. The particles are represented as bat individuals, and the predatory process of bat population is simulated to solve the problem of particle dilution in particle filter technology; the theoretical model of battery state space is constructed by combining the second-order Thevenin battery model, and the related parameters of battery are identified; the SOC is estimated by using BA-PF algorithm and standard PF algorithm under pulse current condition. The experimental results show that, compared with the traditional PF algorithm, the SOC estimation accuracy of Ni-Cd alkaline battery based on BA-PF is less than 2%, and it has good adaptability and stability for nonlinear and non-Gaussian characteristics of Ni-Cd alkaline battery.
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