DC Fast Charging Optimization for Capacity Fade Minimization

Abstract

DC fast charging is a critical step to support the recharging demands of electric vehicles and increase their penetration in the market. However, compared to normal Level 1 or 2 charging, DC fast charging imposes additional battery capacity fade which can result in premature aging of the battery, reducing its useful life. This paper proposes a computationally efficient, meta-heuristic approach to optimize the charging C-Rate profile while considering battery degradation associated with not only the charging but also the expected drive cycle following charging. The battery and its degradation are modeled with a semi-empirical, physics-based approach which yields a high accuracy and is computationally efficient. The meta-heuristic approach to optimize the charge profile is first validated for a simplified case with Dynamic Programming. To demonstrate the effectiveness of the approach in attenuating the battery aging, a benchmark case with 15 minutes of constant current charging of a Lithium Iron Phosphate battery is set. A nearly 1% capacity fade improvement is obtained for a single charge-discharge cycle after charging C-Rate optimization, which would generate significant benefit over the electric vehicle life.