Model Predictive Control-Based Energy Management System for a Hybrid Electric Agricultural Tractor
Gonzalo Curiel‐Olivares, Scott C. Johnson, G. Escobar, R. Schacht-Rodríguez
Abstract
In this work, a model predictive control (MPC) based energy management system (EMS) is designed and implemented to control the powertrain power flow of a series hybrid electric agricultural tractor. The proposed MPC-based EMS considers the battery SoC regulation and the fuel consumption minimization subject to power sources constraints. In addition to the control objectives established in the MPC, the analysis of the results shows the influence of the proposed scheme on the battery state of health (SoH), the battery temperature, the fuel economy and the engine performance based in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">break specific fuel consumption</i> (BSFC) map. For comparison purposes, a conventional rule-based (RB) EMS is also implemented. The results show that the MPC-EMS can achieve the main objectives with 7.2% fuel reduction while satisfactorily managing the systems constraints, and positively impacting the battery SoH and temperature in comparison with the RB-EMS.