Battery SOH (State of Health)

Battery SOH (State of Health) is a key metric indicating an EV battery's current energy storage and power delivery capability relative to its brand-new state, typically expressed as a percentage. As one of the core monitoring parameters within the Battery Management System (BMS), SOH quantitatively tracks the battery's performance throughout its operational lifecycle, directly impacting driving range, vehicle safety, and resale value assessment.

Definition and Measurement Methods

Globally, there is no single standardised definition for SOH, though it is primarily evaluated across several key parameters, including capacity, energy output, internal resistance, cycle count, and peak power.

Capacity-based definition is the most widely adopted approach: SOH = Current Maximum Usable Capacity / Rated Capacity × 100%. A brand-new battery has an SOH of 100%. Over time and with continuous charge-discharge cycles, internal active materials degrade and internal resistance rises, leading to a steady drop in maximum usable capacity and a corresponding decline in SOH. Within the automotive industry, it is widely accepted that once SOH drops below 80%, the traction battery no longer meets automotive performance standards and requires replacement or decommissioning.

Internal resistance-based definition relies on the principle that rising internal resistance is a key sign of battery degradation: SOH = (REOL - RC) / (REOL - Rnew) × 100%, where REOL represents internal resistance at end-of-life, Rc is current internal resistance, and Rnew is the resistance when brand-new. Because internal resistance is heavily influenced by temperature and State of Charge (SOC), it is challenging to measure accurately in real-world conditions, making this method less practical.

Other measurement metrics include the energy-based definition (the ratio of current maximum discharge energy to that of a brand-new battery) and the remaining cycle life definition.

Key Factors Affecting SOH

Battery degradation is a gradual, long-term process driven by a combination of factors.

Temperature is the primary factor influencing battery health. High operating temperatures accelerate irreversible internal chemical reactions, thickening the SEI layer and reducing active materials, thereby speeding up capacity loss. Conversely, while cold temperatures slow down certain secondary reactions, they increase internal resistance and cut usable capacity; charging in low temperatures may also cause lithium plating, resulting in permanent cell damage.

Charge-discharge C-rate plays a direct role in battery lifespan. Testing shows that cycling an 18650 cell 300 times at varying discharge rates leads to capacity degradation of 9.5%, 13.2%, and 16.9%, alongside internal resistance spikes of 12.4%, 18.3%, and 27.7%, respectively. High C-rate charging and discharging generate excessive heat, accelerating the ageing process.

Depth of discharge (DoD) and state-of-charge windows are equally crucial. Industry experts advise maintaining daily SOC levels between 20% and 80% to avoid overcharging and deep discharging, which helps maximise long-term battery health.

SOH Estimation Methods

Because battery SOH cannot be measured directly, it must be estimated using computational models or algorithms. Mainstream methods fall into the following categories:

Direct measurement: Involves laboratory-grade testing of key parameters like capacity or internal resistance to evaluate SOH with high precision. However, this approach is difficult to execute in real-time on-board vehicle applications.

Model-based estimation: Encompasses electrochemical models based on internal chemical mechanisms and equivalent circuit models (ECM) simulating the battery as an electrical network. SOH is estimated by constructing dynamic battery models; however, high computational complexity and strict laboratory testing constraints limit real-world in-vehicle implementation.

Data-driven approach: Leverages artificial intelligence and machine learning trained on historical operational data to identify battery degradation trends. Rather than relying on physical electrochemical mechanisms, it maps the relationship between operating parameters and SOH via big data analytics. Modern research utilising real-world EV discharge data alongside ensemble learning techniques has successfully reduced estimation error by around 14%, demonstrating high practical adaptability.

Economic Value

Traction batteries account for 30% to 50% of an electric vehicle's total manufacturing cost, meaning SOH directly dictates the vehicle's residual value. Market estimates indicate that out-of-warranty EV battery replacement costs range between RM50,000 and RM230,000—roughly half the price of a brand-new vehicle. Accurately assessing SOH is therefore vital not only for range and safety, but also for used EV valuation, second-life repurposing, and battery recycling. The new EU Battery Regulation (EU 2023/1542) now strictly mandates that Battery Management Systems must provide up-to-date metrics determining battery health.