Dual Estimation Strategy for New and Aged Electric Vehicles Batteries

Abstract

The use of hybrid (HEVs) and electric vehicles(EVs) has become more prevalent around the world in the last decade. These vehicles commonly use lithium-ion batteries due to their high energy density. They also utilize battery management systems (BMSs), which rely on continuous real-time monitoring and control, to ensure safe operation. The BMS acquires accurate State Of Charge (SOC) and State Of Health (SOH) estimates. For these, battery models that are identified and updated at various states of life from new to aged are required. In this paper, a dual strategy for both parameter and SOC estimation is proposed using a third-order equivalent circuit-based battery model (OCVR-3RC). The strategy employs a square-root recursive least squares (SR-RLS) method to identify the parameters related to SOC. The smooth variable structure filter (SVSF) is then used as an estimation strategy for obtaining the battery SOC. The efficacy of the proposed algorithm is verified by applying it to experimental data from an extensive aging test.