Chao Lyu

Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD) and parallel FOR loop (PARFOR), is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

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.

An initial implementation of testability analysis based on multi-signal flow graph model

This paper discusses the multi-signal flow graph model and the testability analysis method based on this model. The modeling process of the multi-signal model, the dependency matrix generation method of the failure-test and the details of the testability analysis are illustrated by use of several examples. The results got in the testability analysis are also validated. It is demonstrated that the testability analysis method based on multisignal model is easy to be implemented in computer-aided analysis, which helps to develop the testability analysis software tool in future.

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.

Multi-physics modeling of lithium-ion batteries and charging optimization

A multi-physics model is developed based on P2D model, including the electrochemical part, thermal part and the temperature distribution. It can simulate the physical and chemical phenomena from the scale of the active particles to the scale of whole battery. The charging optimization is also investigated, two internal characteristics, which can only be calculated by the proposed model, are treated as additional optimization objectives.

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 novel parameters acquisition method based on electrochemical impedance spectroscopy mathematical model in lithium ion cell

Electrochemical impedance spectroscopy (EIS) is a widely used technique in presenting the complex impedance character in the frequency domain of the lithium-ion cells, and it can be used to decouple the interfacial reaction, species transport, and lithium ion diffusion process effectively. Meanwhile, it also can be used to provide the support for judging the health status of the cells. The EIS mathematical model can precisely reflect the internal reaction mechanism in lithium-ion cells. Using the model, the cell parameters can be obtained without disassembling cells, with the help of parameter identification technology. In this paper, Genetic Algorithm considering the parameter sensitivity analysis is used to identify the parameters. A novel identification strategy, which distinguishes different parameters in different frequency ranges, is proposed in detail. Finally, the application of the EIS mathematical model in studying the variation trend of the cell parameters with the aging of the cells is shown.

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.

The design of a four DOFs light manipulator used for a dangerous environment detection robot

This paper describes the work principle, structure and drive system design methods for a four degrees of freedom manipulator with strong load capacity, light weight and high rotary accuracy, and carries out a finite element analysis on the key parts of the arm by the software of ANSYS. The simulation results shows that the performances of all the designed parts can meet the design requirements.