This paper presents a battery charge equalization algorithm for lithium-ion battery in EV applications to enhance the battery''s performance, life cycle and safety.
AI Customer ServiceEqualization charging is a specialized process in the maintenance of lead-acid batteries that goes beyond standard charging methods. This technique is critical for optimizing
AI Customer ServiceEqualization is complete when specific gravity values no longer rise during the gassing stage; Battery voltage during an equalization charge should be allowed to rise to 2.65V per cell +/-
AI Customer ServiceThroughout this section, we consider a general charging scenario in which a battery pack can be charged using a variety of power sources, such as the a photovoltaic
AI Customer ServiceCharge imbalance reduces the power performance and available energy of battery packs. Hence, it is necessary to perform battery equalization. This article proposes an active equalization
AI Customer ServicePack capacity and consistency in the fresh or aged state are significantly improved after battery equalization. In the real battery module experiment, the maximum
AI Customer ServiceThis paper presents a battery charge equalization algorithm for lithium-ion battery in EV
AI Customer ServiceCapacity-based equalization strategies take C C during charging and C R during discharging as equalization variables to determine whether a battery pack is consistent or not,
AI Customer ServicePack capacity and consistency in the fresh or aged state are significantly
AI Customer ServiceAs shown in Figure 11(a), the figure identifies 1 is the drive power module, mainly used for charging each battery in the battery pack; 2 for the electronic load module,
AI Customer ServiceThe following three constraints should be satisfied in the charging process to guarantee the stability of the battery pack system and extend battery lifetime: the SOC
AI Customer ServiceThe control strategy adopts the open-circuit voltage (OVC) of the battery
AI Customer ServiceThe control strategy adopts the open-circuit voltage (OVC) of the battery and the state of charge (SOC) of the battery as the equalization variables, and selects the
AI Customer ServiceFirst, it balances the cells in the battery pack so that they are all in the same state of charge. Second, it helps to prevent sulfation, which is when lead sulfate crystals build up on the electrodes and reduce capacity. To
AI Customer ServiceCharge imbalance reduces the power performance and available energy of battery packs.
AI Customer ServiceBattery balancing equalizes the state of charge (SOC) across all cells in a multi-cell battery pack. This technique maximizes the battery pack''s overall capacity and lifespan
AI Customer ServiceWhen cells within a battery pack have different charge levels, it can lead to a range of issues, including reduced capacity, decreased efficiency, and diminished overall
AI Customer ServiceLithium-ion battery pack capacity directly determines the driving range and dynamic ability of electric vehicles (EVs). However, inconsistency issues occur and decrease the pack capacity
AI Customer ServiceThe equalization control strategy and the equalization topology were integrated into the equalization control test platform of lithium battery pack developed by our research
AI Customer ServiceTaking the battery SOC as an example of the equilibrium variable, the battery SOC monitoring module will monitor the SOC in real time, When the battery''s state of charge
AI Customer ServiceTo address this issue, this work proposes an active equalization scheme for battery packs based on dynamic route planning. Specifically, an active equalization topology is
AI Customer ServiceThe difference of inconsistency for lithium-ion battery pack equalization is determined based on the uniform charging cell voltage curves hypothesis. Stability of the
AI Customer ServiceTo our knowledge, this is the first work to achieve series-connected battery pack active equalization by fusion of data-driven residual capacity online estimation and global
AI Customer ServiceActive equalization based on capacity during charging and discharging. Capacity-based equalization strategies take C C during charging and C R during discharging as equalization variables to determine whether a battery pack is consistent or not, and then equalize based on capacity.
The equalization strategy is embedded in a real BMS for practical application analysis. Lithium-ion battery pack capacity directly determines the driving range and dynamic ability of electric vehicles (EVs). However, inconsistency issues occur and decrease the pack capacity due to internal and external reasons.
Finally, the results of simulation and experiment both show that the equalization strategy not only maximizes pack capacity, but also adapts to different consistency scenarios. Pack capacity and consistency in the fresh or aged state are significantly improved after battery equalization.
After a thorough literature survey, it was found that there are many battery pack equalization strategies developed, but the systematic review and classification are missing. Some studies simply classify the equalization strategies based on the equalization variable, such as voltage, SOC, and capacity.
Charge imbalance reduces the power performance and available energy of battery packs. Hence, it is necessary to perform battery equalization. This article proposes an active equalization circuit and a novel equalization strategy to achieve energy redistribution.
L. Dung proposed a charging equalization method that adapts itself to the aging conditions. It used the voltage difference among cells to adjust the equalization current, which not only maximized the total capacity but also slowed down the battery pack aging rate.
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