Active battery cell equalization based on residual available energy maximization

Summary Differences in the environment and parameters of lithium‐ion battery (LiB) cells may lead the residual capacity between the battery cells to be inconsistent, and the battery cells may be damaged due to overcharging or overdischarging. In this study, an active balancing method for charging and discharging of LiB pack based on average state of charge (SOC) is proposed. Two different active balancing strategies are developed according to the different charging and discharging states of LiB pack. When the LiB pack is charging, charging balance strategy is performed, wherein the battery cells whose SOC is higher than the average SOC of the LiB pack are balanced to increase the charging capacity of the entire LiB pack. When the LiB pack is discharging or static standing, discharging balance strategy is performed, wherein the batter cells whose SOC is lower than the average SOC of the LiB pack are balanced to increase the discharging capacity of the entire LiB pack. The experimental results show that the proposed active balancing method can reduce the inconsistency of residual energy between the battery cells and improve the charging and discharging capacity of the LiB pack.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Active cell balancing of lithium‐ion battery pack based on average state of charge

Zhang

et al. 2020

“…However, it is easily affected by the internal parameters of the battery and long‐term battery usage will lead to unstable equalization control performance. Battery capacity equalization scheme has the advantage of maximizing capacity, but it is not suitable for online equalization as the battery capacity can only be obtained under static conditions . The SOC‐based battery equalization can reduce battery inconsistency, optimize battery energy configuration, and improve battery pack safety, but the estimation is difficult .…”

Section: Introductionmentioning

confidence: 99%

Equalization of series connected lithium‐ion batteries based on back propagation neural network and fuzzy logic control

Wang

Qin²,

Zhao

et al. 2020

Summary In this article, a nondissipative equalization scheme is proposed to reduce the inconsistency of series connected lithium‐ion batteries. An improved Buck‐Boost equalization circuit is designed, in which the series connected batteries can form a circular energy loop, equalization speed is improved, and modularization is facilitated. This article use voltage and state of charge (SOC) together as equalization variables according to the characteristics of open‐circuit voltage (OCV)‐SOC curve of lithium‐ion battery. The second‐order RC equivalent circuit model and back propagation neural network are used to estimate the SOC of lithium‐ion battery. Fuzzy logic control (FLC) is used to adjust the equalization current dynamically to reduce equalization time and improve efficiency. Simulation results show that the traditional Buck‐Boost equalization circuit and the improved Buck‐Boost equalization circuit are compared, and the equalization time of the latter is reduced by 34%. Compared with mean‐difference algorithm, the equalization time of FLC is decreased by 49% and the energy efficiency is improved by 4.88% under static, charging and discharging conditions. In addition, the proposed equalization scheme reduces the maximum SOC deviation to 0.39%, effectively reducing the inconsistency of batteries.

“…However, after working for a period, there may be problems of excessive capacity degradation or internal resistance increase of a single cell or a few cells, resulting in inconsistencies that will lead to the performance degradation of the battery pack's available capacity, service life, and so on. Inconsistency is a decisive factor in the performance of the entire battery packs, affecting the travel and drive performance of electric vehicles . At present, the balance management control of battery packs is the main method to solve the inconsistency problem, so the balance management of the battery pack is of great importance.…”

Section: Introductionmentioning

confidence: 99%

Active equalization control strategy of Li‐ion battery based on state of charge estimation of an electrochemical‐thermal coupling model

Lin

Wang

et al. 2020

Summary Aiming at solving the problem of poor battery cell consistency caused by excessive decay of cell capacity or increased internal resistance during the operation of lithium‐ion battery packs for vehicles, the paper proposes an active equalization control with 12‐V power supply as an equalization energy source, which achieves efficient energy replenishment of individual cells with low power. The electrochemical‐thermal coupling model of lithium‐ion battery is built, and the order reduction of large‐scale system theory ensures that the model had higher accuracy and lower amount of calculation, which is suitable for vehicle battery management system (BMS). Then the extended Kalman filter algorithm is used to calculate the real‐time state of charge (SOC) of each cell and set as an equalization variable. The equalization simulation circuit is built with MATLAB/Simulink, the experimental platform of active equalization system for battery packs is constructed, and the battery packs are tested for equalization in static state. The simulation and experimental results show that the proposed active equalization control strategy can rapidly improve the voltage inconsistency between single cells, and the energy transfer efficiency can reach about 85% during the equalization process.