A real-time Energy Management System (EMS) is presented in this paper, which aims at minimizing the operating costs of a Hybrid Electric Vehicle (HEV) equipped with different energy storage units (fuel cell, supercapacitors, batteries). The proposed EMS manages all HEV operating constraints properly through a Model Predictive Control (MPC) approach, which identifies the allowable ranges of each variable based on system modelling and actual HEV operating conditions. The optimization is then carried out by means of suitable look-up tables, which are accessed in accordance with the variable ranges previously computed. The effectiveness of the proposed MPC-based EMS is verified through numerical simulations, which also regard a rule-based EMS for comparison purposes.

An MPC-based Energy Management System for a Hybrid Electric Vehicle

Serpi A;Porru M
2020-01-01

Abstract

A real-time Energy Management System (EMS) is presented in this paper, which aims at minimizing the operating costs of a Hybrid Electric Vehicle (HEV) equipped with different energy storage units (fuel cell, supercapacitors, batteries). The proposed EMS manages all HEV operating constraints properly through a Model Predictive Control (MPC) approach, which identifies the allowable ranges of each variable based on system modelling and actual HEV operating conditions. The optimization is then carried out by means of suitable look-up tables, which are accessed in accordance with the variable ranges previously computed. The effectiveness of the proposed MPC-based EMS is verified through numerical simulations, which also regard a rule-based EMS for comparison purposes.
2020
978-1-7281-8959-8
Batteries; Cost function; Electric vehicle; Energy management; Fuel cells; Optimization; Predictive control; Supercapacitors
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/302516
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