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

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.

Plant and Controller Optimization for Power and Energy Systems With Model Predictive Control

“…In addition, to optimize controller parameters, the controller design variables 𝝓 ∈ ℝ 𝑁 𝜙 are defined [52]. These have minimum and maximum bounds 𝝓 and 𝝓, respectively.…”