An electric vehicle (EV) battery state of charge (SOC) represents energy levels as a percentage. Analogous to an internal combustion engine (ICE) fuel gauge, SOC clearly indicates available energy that directly corresponds to the driving range. This article explains how SOC is calculated and explores the different methods used to determine these calculations. It also highlights SOC’s critical role in EVs and describes how various calibration techniques ensure continuous, accurate measurement. 

Calculating EV SOC
EV battery SOC is calculated by dividing the current charge (Q) by its total capacity (Q_total), then multiplying the result by 100 to express it as a percentage.

This formula provides a quick estimate of the battery’s energy relative to its full capacity. However, accurate and precise SOC measurements require advanced battery management systems (BMS) to analyze complex variables such as voltage, current, and temperature. A typical BMS consists of sensors, actuators, controllers, and signal lines, all working together to monitor and regulate essential battery parameters, from SOC and state of health (SOH) to state of power (SOP) and state of life (SOL). 

The methodology of determining EV SOC
Different techniques determine EV battery SOC. Coulomb Counting, an ampere-hour integral method, effectively quantifies electric charge in amperes over time, providing dynamic, continuous updates. Open circuit voltage (OCV) rapidly assesses remaining energy by calculating the direct relationship between voltage and charge level. Coulomb Counting, however, can accumulate errors over time due to sensor drift or battery behavior variations, while OCV may be affected by temperature fluctuations and battery aging.

Sophisticated model-based approaches, including electrochemical impedance spectroscopy (EIS) and equivalent circuit models (ECM), conduct in-depth SOC analysis by simulating battery electrochemical reactions and electrical behavior. These methods assess internal resistance, capacity, and other key parameters, providing a comprehensive view of SOC across operational conditions.

Kalman Filtering, another popular model-based technique, integrates data from multiple sensors to precisely estimate SOC, even in dynamic environments. However, the accuracy of Kalman Filtering is susceptible to external factors such as sensor drift, extreme temperature changes, and variations in battery behavior.

Most EVs use a combination of different methods and techniques to accurately gauge SOC. Coulomb Counting and OCV rapidly provide basic data, while EIS, ECM, and Kalman Filtering offer more detailed and precise information. Estimation models and strategies, such as electrochemical, recursive, one-dimensional (1D), and pseudo two-dimensional (P2D), further refine calculations.

Additionally, emerging AI and ML applications, including neural networks and support vector machines, process extensive datasets continuously to improve SOC accuracy. All SOC methods and techniques should be recalibrated over time.

The importance of SOC recalibration
SOC recalibration is recommended after battery replacements, software updates, or sensor malfunctions. This process typically involves adjusting or updating BMS algorithms to align with battery capacity, a variable that changes with use and aging. One common calibration method includes resetting BMS SOC estimation parameters based on data from a full charge and discharge cycle.

Additionally, precise voltage measurements, taken at specific states of charge, help further fine-tune SOC estimation algorithms. 

The crucial role of SOC in EVs
Effectively managing SOC helps optimize EV batteries’ efficiency, performance, and lifespan. For example, SOC plays a crucial role in:

• Preventing damage: By maintaining SOC between 20% and 80%, an EV BMS prevents excessive battery wear and tear, extending SOH, capacity, and operational lifespan. The BMS also relies on accurate SOC readings to reduce the risk of battery cell damage caused by full charges and deep discharges. 
• Maximizing performance: EV batteries deliver optimal performance when operated within specific SOC ranges. Although these may vary depending on battery chemistry and design, most EV batteries see efficient power delivery and robust acceleration within the 20% to 80% SOC range. 
• Estimating driving range: SOC directly impacts EV driving range, essential for effective and safe trip planning. Notably, EV driving ranges are also impacted by other factors, such as battery capacity and energy efficiency.
• Optimizing energy efficiency: Precise SOC measurements minimize energy waste while maximizing regenerative braking, extending driving range, and improving overall energy efficiency.
• Ensuring charge safety: The BMS uses SOC readings to modulate EV battery charging rates, applying techniques such as trickle charging and controlled fast charging to protect battery life. It also ensures balanced charging of individual cells, guided by a dynamic charging curve that optimally adjusts current and voltage to maintain battery health and prevent overcharging. 

Summary
EV battery SOC clearly indicates available energy directly corresponding to driving range and efficiency. Maintaining SOC between 20% and 80% prevents excessive battery wear and tear while maximizing performance. EV battery SOC is determined using a diverse combination of methods and techniques, ranging from Coulomb Counting and OCV to Kalman Filtering, EIS, and ECM.  

References
What is State of Charge (SoC) of an EV Battery?, everythingPE
Review on the State of Charge Estimation Methods for Electric Vehicle Battery, MDPI
SOC Estimation of Lithium-Ion Battery for Electric Vehicle Based on Deep Multilayer Perceptron, Hindawi
What is an Electric Car Charging Curve?, Gridserve
Lithium-Ion State of Charge (SoC) Measurement, Power Tech Systems