Research On Charge State And Active Equalization Technology Of Lithium-Ion Battery

With the consumption of non-renewable energy and the intensification of environmental pollution,the development of battery performance and promotion of its application has been widely concerned by the competent departments and researchers.At present,there are a variety of secondary batteries such as lead-acid batteries,nickel-metal hydride batteries,and lithium-ion batteries on the market.Due to the advantages such as high power,high energy density,long cycle life,low discharge rate and moderate price,lithium-ion batteries are widely used in the fields of transportation power,electric power storage,mobile communication,new energy storage,aerospace and military industry.Therefore,it is of important theoretical significance and practical value to study the related technologies of lithium-ion batteries.This paper mainly studies the state-of-charge(SOC)estimation method and the active balancing technology of lithium-ion batteries.Based on the analysis of commonly used SOC estimation methods and equalization methods,a new algorithm based on whales and genetic algorithms is proposed.Optimizing the weights and thresholds of the Elman neural network to estimate the SOC of lithium-ion batteries;Then,using the estimated SOC value as one of the equilibrium criteria for the equilibrium of lithium-ion batteries,an active balancing circuit of distributed energy storage based on fuzzy control was designed,produced and debugged.The main work are as follows:(1)Introduced the structure,principle,characteristic parameters and monomer model of lithium-ion batteries,as well as the research progress of SOC estimation method and active equalization technology for lithium-ion batteries;(2)A SOC estimation method that combines the whale algorithm and genetic algorithm to optimize the weight and threshold of the Elman neural network is proposed and verified by experiments.A three-input one-output training model was designed,using battery current,voltage,and temperature as model input values,SOC as output value,and Matlab was used to simulate the estimation method;An online monitoring system for battery parameters is designed to collect the learning and test data of Elman neural network.Experiments show that this estimation method has high estimation accuracy,and its average error is less than 1 %;(3)The energy storage characteristic of inductance is utilized to realize the power balance between batteries: a lithium-ion battery component layer balance circuit based on distributed energy storage is designed,which not only achieves the balance of battery power,but also shortens the balance time.The balance control adopts the pulse width modulation(PWM)method to control the switching tube,and controls the on-off time of the switching tube based on the voltage difference between the batteries.Build a hardware platform to verify the performance of the designed equalization circuit.The results show that the equalization error is less than 0.02 V;(4)A balanced control strategy based on fuzzy control is proposed: a fuzzy controller is added to the circuit to establish a two-input one-output fuzzy control system.The SOC estimation value and voltage of the single lithium ion battery are taken as input,and the output controls the switching time of the power tube,so as to realize the adjustment of the balance current.Simulink is used to simulate the equalization method,and the results show that the equalization circuit using this control strategy not only reduces energy consumption,but also shortens the equalization time.