Real-Time Optimization for Power Management Systems of a Battery/Supercapacitor Hybrid Energy Storage System in Electric Vehicles

Batteries mounted on electric vehicles (EVs) are often damaged by high peak power and rapid charging/discharging cycles, which are originated from repetitive acceleration/deceleration of vehicles particularly in urban situations. To reduce battery damage, the battery/supercapacitor (SC) hybrid energy storage system (HESS) has been considered as a solution because the SC can act as a buffer against large magnitudes and rapid fluctuations in power. While the traditional purpose of employing the HESS in EVs is to minimize the magnitude/variation of battery power or power loss, the previous approaches proposed for controlling the HESS have some drawbacks; they neither consider these objectives simultaneously nor reflect real-time load dynamics for computing the SC reference voltage. In this paper, we present a power control framework consisting of two stages: one for computing the SC reference voltage and another for optimizing the power flowing through the HESS. In the presented framework, we propose a methodology for calculating the SC reference voltage considering the real-time load dynamics without given future operation profiles. In addition, we formulate the HESS power control problem as a convex optimization problem that minimizes the magnitude/fluctuation of battery power and power loss at the same time. The optimization problem is formulated so that it can be repeatedly solved by general solvers in polynomial time. Simulation results carried out on MATLAB show that the magnitude/variation of battery power and power loss can be concurrently reduced in real time by the proposed framework.