Junfu Li

A Method of Remaining Capacity Estimation for Lithium-Ion Battery

Combining particle filter (PF) with sample entropy feature of discharge voltage, a method of remaining capacity estimation for lithium-ion battery is proposed. The sample entropy calculated from discharge voltage curve can serve as an indicator for assessing the condition of battery. Under a certain working condition, a functional relationship between sample entropy and discharge capacity is created and estimations computed from the function are taken as observations to propagate particles in PF. The results indicate that the algorithm enhances the accuracy. Due to the establishment of functions at different discharge rates and temperature modification, prognostic accuracy of discharge capacity has been improved under multi-operating working conditions.

Model-based method for estimating LiCoO 2 battery state of health and behaviors

Simplified mechanistic models can accurately simulate battery behaviors and are more suitable for studies on mechanistic parameters. Battery remaining useful life can be predicted by analyzing the variations of parameters at different aging stages. The main work of this paper is listed below: (i) Parameters of mechanistic model at different stages are analyzed according to their variation laws, (ii) Based on the variations of these selected parameters, battery discharge behaviors are predicted. The simulated results show good agreement with measurements.

A novel method for capacity fade analysis of lithium-ion batteries based on multi-physics model

Detailed information of the capacity fade mechanisms can be very beneficial for the prognostics and health management (PHM) study of lithium-ion batteries. This paper reports a novel capacity fade analysis method. The parameter degradation of multi-physics model is achieved, and the three main factors of capacity fade is quantitatively calculated by using the obtained parameters. The results show that the loss of active material and the loss of Li inventory is the main reason of capacity fade at high temperature and room temperature, respectively. And the proposed method can further help improving battery (pack) management, reliability and safety.

A research of thermal coupling model for lithium-ion battery under low-temperature conditions

Electrochemical models and equivalent circuit models have been the most common choices for simulation of the performance of lithium-ion battery. However, most models do not consider the temperature effect on the battery parameters, which leads to large simulation error when battery is under subzero operation conditions. Actually, low ambient temperature operation condition is inevitable for EVs and HEVs in cold-climate of some regions. Fundamentally, low-temperature conditions lead to a slowdown of the chemical reactions, affecting the charge-transfer kinetics and leading to low electrolyte conductivity and a decreased diffusivity of lithium ions within the negative-potential electrode(anode). In this paper, the relationship between temperature-dependent parameters and temperature at low temperatures was established. An improved model based on electrochemical-thermal coupling model (ETCM) was proposed to accurately simulate battery performance. Experimental data and the simulation of a battery proved that the proposed model can precisely simulate the battery performance at low temperatures. The results obtained in this paper are quite useful for battery management system.

A healthy charging method based on estimation of average internal temperature using an electrochemical-thermal coupling model for LiFePO 4 battery

Constant current-constant voltage (CC-CV) charging and pulse current charging are the usual methods for charging Li-ion batteries. Because we are lack of the direct in-situ measurement of Li-ion batterys internal state, both of the two charging methods are controlled without feedbacks from inside of the battery. A new charging method is proposed in this paper based on electrochemical-thermal coupling model (ECTM), taking its advantage of being able to predict not only external but also internal behaviors of Li-ion batteries with satisfactory accuracy. The benefit of the method lies in that the rate of side reactions evoking degradation can be slowed down by restricting the average internal temperature in the radius direction to be lower than a preset value. To achieve this method, the heat generation rate that significantly influences the average temperature of the battery is controlled by cutting off the charging current. With the proposed charging strategy, the useful lifetime of Li-ion batteries can be prolonged while the charging speed is also guaranteed.