A review on the key issues for lithium-ion battery management in electric vehicles

https://hal-cea.archives-ouvertes.fr/cea-01791260/document

A review on lithium-ion battery ageing mechanisms and estimations for automotive applications

Due to increasing concerns about global warming, greenhouse gas emissions, and the depletion of fossil fuels, the electric vehicles (EVs) receive massive popularity due to their performances and efficiencies in recent decades. EVs have already been widely accepted in the automotive industries considering the most promising replacements in reducing CO2 emissions and global environmental issues. Lithium-ion batteries have attained huge attention in EVs application due to their lucrative features such as lightweight, fast charging, high energy density, low self-discharge and long lifespan. This paper comprehensively reviews the lithium-ion battery state of charge (SOC) estimation and its management system towards the sustainable future EV applications. The significance of battery management system (BMS) employing lithium-ion batteries is presented, which can guarantee a reliable and safe operation and assess the battery SOC. The review identifies that the SOC is a crucial parameter as it signifies the remaining available energy in a battery that provides an idea about charging/discharging strategies and protect the battery from overcharging/over discharging. It is also observed that the SOC of the existing lithium-ion batteries have a good contribution to run the EVs safely and efficiently with their charging/discharging capabilities. However, they still have some challenges due to their complex electro-chemical reactions, performance degradation and lack of accuracy towards the enhancement of battery performance and life. The classification of the estimation methodologies to estimate SOC focusing with the estimation model/algorithm, benefits, drawbacks and estimation error are extensively reviewed. The review highlights many factors and challenges with possible recommendations for the development of BMS and estimation of SOC in next-generation EV applications. All the highlighted insights of this review will widen the increasing efforts towards the development of the advanced SOC estimation method and energy management system of lithium-ion battery for the future high-tech EV applications.

A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations

With the rapidly evolving technology of the smart grid and electric vehicles (EVs), the battery has emerged as the most prominent energy storage device, attracting a significant amount of attention. The very recent discussions about the performance of lithium-ion (Li-ion) batteries in the Boeing 787 have confirmed so far that, while battery technology is growing very quickly, developing cells with higher power and energy densities, it is equally important to improve the performance of the battery management system (BMS) to make the battery a safe, reliable, and cost-efficient solution. The specific characteristics and needs of the smart grid and EVs, such as deep charge/discharge protection and accurate state-of-charge (SOC) and state-of-health (SOH) estimation, intensify the need for a more efficient BMS. The BMS should contain accurate algorithms to measure and estimate the functional status of the battery and, at the same time, be equipped with state-of-the-art mechanisms to protect the battery from hazardous and inefficient operating conditions.

Battery Management System: An Overview of Its Application in the Smart Grid and Electric Vehicles

A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures

Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

The charging and discharging characteristics of lead-acid batteries are investigated to learn the relationship between the state-of-charge (SOC) and the dynamically changed open-circuit voltage Experimental results indicate that the open-circuit voltage of the lead-acid battery varies methodically with the charging or discharging rates and the duration since they have been disconnected from the load or charger Accordingly, a dynamic open-circuit voltage method by taking account of the open-circuit time and the previous charging/discharging rate is capable of more precisely estimating the SOC in a shorter time Experiments that emulate practical operations are carried out to demonstrate the effectiveness and accuracy of the proposed method

Yi-Ping Chen

Papers

Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries

State-of-charge estimation for lead-acid batteries based on dynamic open-circuit voltage