Direct Comparison using Coulomb Counting and Open Circuit Voltage Method for the State of Health Li-Po Battery

Electric cars have undergone many developments in the current digital era. This is to avoid the use of increasingly scarce fuel. Recent studies on electric cars show that battery estimation is an interesting topic to be implemented directly. The battery estimation strategy is carried out by the Battery Management System (BMS). BMS is an indispensable part of electric vehicles or hybrid vehicles to ensure optimal and reliable operation of regulating, monitoring, and protecting batteries. A reliable BMS can extend battery life by setting voltage, temperature, and charging and discharging current limits. The main estimation strategy used by BMS is battery fault, SOH, and battery life. Battery State of Health (SOH) is part of the information provided by the BMS to avoid battery damage and failure. SOC is the proportion of battery capacity SOH is a measure of battery health. This study aims to develop a method for estimating SOH simultaneously using Coulomb Counting and Open Circuit Voltage (OCV) algorithms. The battery is modeled to obtain battery parameters and components of internal resistance, capacitance polarization and OCV voltage source. Several tests were implemented in this research by applying the constant current (CC)-charge CC-discharge test. The state-space system is then formed to apply the Coulomb Counting and OCV algorithms so that SOH can be estimated simultaneously. The OCV-SOC function is obtained in the form of a tenth order polynomial and the battery model parameters say that these parameters change with the health of the battery. The results of the model validation are able to accurately model the battery with an average relative error of 0.027%. Coulomb Counting resulted in an accurate SOH estimation with an error of 3.4%

A Flyback Converter-based Hybrid Balancing Method for Series-Connected Battery Pack in Electric Vehicles

An active balancing method based on two flyback converters is proposed for series-connected battery pack. Balanced energy can be transferred between the whole battery and any single cell. The proposed topology reduces the number of energy storage components, the volume and the cost of the balancing system. And it has the characteristics of fast balancing speed and high balancing efficiency. Based on the topology, a dual-objective hybrid control strategy is proposed, which can reduce the highest voltage and boost the lowest voltage in the charging or discharging process of the cells simultaneously, so as to improve the balancing speed. Simulation and experimental results show that the proposed method has a good balancing effect and can significantly improve the consistency of series battery pack. This work is potentially significant in terms of improved reliability of battery packs and savings of costs and lives in safety-critical applications

The heating triangle: A quantitative review of self-heating methods for lithium-ion batteries at low temperatures

Lithium-ion batteries at low temperatures have slow recharge times alongside reduced available power and energy. Battery heating is a viable way to address this issue, and self-heating techniques are appealing due to acceptable efficiency and speed. However, there are a lack of studies quantitatively comparing self-heating methods rather than qualitatively, because of the existence of many different batteries with varied heating parameters. In this work, we review the current state-of-the-art self-heating methods and propose the heating triangle as a new quantitative indicator for comparing self-heating methods, towards identifying/developing effective heating approaches. We define the heating triangle which considers three fundamental metrics: the specific heating rate (°C·g·J−1), coefficient of performance (COP) (−), and specific temperature difference (°C·hr), enabling a quantitative assessment of self-heating methods using data reported in the literature. Our analysis demonstrates that very similar metrics are observed for the same type of self-heating method, irrespective of the study case, supporting the universality of the proposed indicator. With the comparison insights, we identify research gaps and new avenues for developing advanced self-heating methods. This work demonstrates the value of the proposed heating triangle as a standardised approach to compare heating methods and drive innovation