Multi-objective Optimal Sizing and Real-time Control of Hybrid Energy Storage Systems for Electric Vehicles

Abstract

Hybrid energy storage system (HESS) with the combination of lithium-ion batteries and supercapacitors has been recognized as a quite appeal solution to face against the drawbacks such as, high cost, low power density and short cycle life of the battery-only energy storage system, which is the major headache hindering the further penetration of electric vehicles. A properly sized HESS and an implementable real-time energy management system are of great importance to achieve satisfactory driving mileage and battery cycle life, however, the introduced sizing and energy management problems are quite complicated and challenging in practice. This work proposed a Bi-level multi-objective sizing and control framework with the non-dominated sorting genetic algorithm-II and fuzzy logic control (FLC) as key components to obtain an optimal sized HESS and a corresponding optimal real-time FLC based EMS simultaneously. In particular, a vectorized fuzzy inference system which allows large scale fuzzy logic controllers operating in parallel is devised for the first time for such kinds of problems to improve the optimization efficiency. At last, the Pareto optimal solutions of different HESSs incorporating both optimal design and control parameters are obtained and compared to show the achieved enhancements.

Critical Review of Intelligent Battery Systems: Challenges, Implementation, and Potential for Electric Vehicles

“…In contrast, the sole consideration of the operating strategy for a fixed design often only provides a suboptimal solution for the entire HBSS. Yu et al [524] propose a multi-objective bi-level optimal design and control framework, in order to find the optimal parameters for a fuzzy-logic-based real-time energy management algorithm. This framework is able to obtain the Pareto optimal solutions of the objective function.…”

Multi-Objective Evolutionary Design of an Electric Vehicle Chassis

“…where T is the motor torque and n m , the rotational speed. The changeover point between maximum torque and constant power (cut-off speed, n m_c ) is defined as: (18) and can be calculated via the following expression:…”

“…Liu et al [ 17 ] optimized an acceleration profile for an electric vehicle, taking into account the energy consumption and percentage of battery capacity loss per kilometer. Yu et al [ 18 ] also considered the battery life in the optimization process of an electric vehicle. In their paper, the sizing and energy management of the battery pack arranged in a hybrid racing vehicle is addressed as a multi-objective optimization problem.…”

Hybrid battery‐ultracapacitor storage system sizing for renewable energy network integration

“…An example of this curve can be found in [31]. The authors of [32] also present a genetic algorithm to size a HESS for EVs considering battery degradation. This algorithm provides multiple sizing solutions with their relationship between the weight and the cycle life of the battery.…”