Predictive SoC Management for Enhanced Recuperation Efficiency in Electric Vehicles

In recent years, the automotive industry has been looking into alternatives for conventional vehicles to promote a sustainable transportation future having a lesser carbon footprint. Electric Vehicles (EV) are a promising choice as they produce zero tail pipe emissions. However, even with the demand for EVs increasing, the charging infrastructure is still a concern, which leads to range anxiety. This necessitates the judicious use of battery charge and reduce the energy wastage occurring at any point. In EVs, regenerative braking is an additional option which helps in recuperating the battery energy during vehicle deceleration. The amount of energy recuperated mainly depends on the current State of Charge (SoC) of the battery and the battery temperature. Typically, the amount of recuperable energy reduces as the current SoC moves closer to 100%. Once this limit is reached, the excess energy available for recuperation is discharged through the brake resistor/pads. This paper proposes a method to minimize the energy wastage due to the SoC constraints by predicting an optimal start SoC. The optimal SoC is calculated in such a way that it maximizes energy recovery during regeneration while taking the route attributes, weather conditions and charger availability into account. On a hilly route, it was noticed that the recuperated energy was 5 times more while using the optimal SoC, compared to the 100% start SoC. This reduction in SoC prevents overcharging and contributes to lesser charging time. Consequently, this approach would positively impact overall battery health, energy efficiency and contribute to promoting sustainability.