A method to estimate battery SOH indicators based on vehicle operating data only

Batteries are multi-physical systems and during actual operating conditions they are submitted to var-iable ambient operating conditions which can affect the dynamic behavior and the degradation. Therefore, a good understanding of the dynamic behavior and the degradation laws under actual operating conditions is the key to a durability improvement and to the development of better energy management strategies. The purpose of the proposed study is to use an experimental database issued from a three years monitoring of a ten postal vehicle fleet to model the batteries with respect to oper-ating conditions. Based on an electrical circuit model, an optimization algorithm and a Kalman filter, the scientific contribution is to propose a simple but efficient method, using vehicle operating data only, to estimate on-board the state of charge and state of health indicators linked to internal resistance and available capacity. The proposed model presents a very good accuracy and state of health indicators estimations show promising results. In the future, the proposed method could be applied on-board to estimate and analyze the state of health during the entire battery lifetime in order to provide an accurate state of charge estimation and to contribute to a better understanding of the degradation laws. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Batteries are complex systems that are affected by variable ambient operating conditions, and understanding their dynamic behavior and degradation laws under actual conditions is essential for durability improvement. This study proposes a method to model batteries based on experimental data from postal vehicles, which shows promising results in estimating state of health indicators linked to internal resistance and available capacity. The proposed model aims to provide accurate state of charge estimation onboard and contribute to a better understanding of battery degradation laws.