Research On Balancing Control Of Lithium-Ion Battery Based On State Of Charge Estimation

The battery management system is one of the core subsystems of electric vehicles,and battery balancing control is a crucial technology in the battery management system to avoid accidents caused by overcharging and overdischarging of battery cells.The state of charge of the battery represents the real-time charge of the battery,which is often selected as the variable of battery balancing control.However,the internal degradation mechanism of the lithium-ion battery system is tightly coupled,the external characteristics are non-linear and time-varying,and it is susceptible to many uncertain factors such as environment and charge/discharge ratio in practical scenarios,which bring significant challenges to battery’s state of charge estimation and balancing control.Therefore,based on adaptive particle filter and immune particle swarm optimization algorithm,the state of charge estimation and balancing control of the lithium-ion battery are researched in this paper.The main research contents are as follows:Firstly,aiming at the problem that the state of charge estimation of lithium-ion batteries is susceptible to many factors,a state of health assisted state of charge estimation method of lithium-ion batteries is proposed.The equivalent circuit model of the lithium-ion battery is established according to the battery mechanism.The H-infinity filter algorithm is presented to realize the online parameter identification of the equivalent circuit model.The battery capacity predicted by the multi-core relevance vector machine is regarded as the actual available capacity.The identified model parameters and predicted capacity are adopted as the parameters of the adaptive particle filter state estimator to realize the accurate state of charge estimation of the lithium-ion batteries.Secondly,a battery balancing control strategy based on immune particle swarm optimization algorithm is proposed for the non-linear time-varying characteristics of the battery balancing control process.The balancing topology circuit and its working mode are analyzed,and the space equation of the switchable charging balancing system is established.The mapping between the state of charge of the lithium-ion battery and the switching variable of balancing control is established.The state of charge balancing problem is transformed into a non-linear integer programming problem,and the optimization problem is L1 regularization.The immune particle swarm optimization algorithm is utilized to solve the balancing control problem to realize the optimal balancing of the battery’s state of charge.Finally,the effectiveness and accuracy of the state of charge estimation algorithm and balancing control algorithm proposed in this paper are verified by the lithium-ion battery cycle aging experiment,public dataset,and balancing experiment platform.