Energy storage and control optimization for an electric vehicle

2018 ◽  
Vol 42 (11) ◽  
pp. 3506-3523 ◽  
Author(s):  
Jony Javorski Eckert ◽  
Ludmila Corrêa de Alkmin e Silva ◽  
Fabio Mazzariol Santiciolli ◽  
Eduardo dos Santos Costa ◽  
Fernanda Cristina Corrêa ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Control Optimization ◽  
And Control

Graph-Based Design and Control Optimization of a Hybrid Electrical Energy Storage System

2020 ◽  
Author(s):  
Cary Laird ◽  
Donald Docimo ◽  
Christopher T. Aksland ◽  
Andrew G. Alleyne
Keyword(s):  
Energy Storage ◽  
Storage System ◽  
Electrical Energy ◽  
Energy Storage System ◽  
Electrical Performance ◽  
Electrical Energy Storage ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Control Optimization ◽  
And Control

Abstract Hybrid energy storage systems are a popular alternative to traditional electrical energy storage mechanisms for electric vehicles. Consisting of multiple heterogeneous storage elements, these systems require thoughtful design and control techniques to ensure adequate electrical performance and minimal added weight. In this work, a graph-based design optimization framework is extended to facilitate design and control optimization of a battery-ultracapacitor hybrid energy storage system. For a given high ramp rate load profile, a hybrid electrical energy storage system consisting of battery and ultracapacitor packs with proportional-integral controllers is considered. A multi-objective optimization problem is formulated to simultaneously optimize sizing and performance of the system by minimizing mass and deviations from ideal controller performance. This optimization is achieved by adjusting the size of the energy storage system and parameters of the feedback controller. A Pareto curve is provided, which exhibits the tradeoffs between sizing and performance of the hybrid energy storage system. Dynamic simulation results demonstrate optimized designs outperform initial designs in both sizing and electrical performance objectives. The design and control optimization approach is shown to outperform a similar sizing optimization approach.

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