MPC Energy Prediction Control Simulation of a Hybrid Electric Vehicle

Abstract

The paper presents a model predictive control (MPC) energy prediction control function simulation environment using virtual controller technology. The MPC energy prediction function is a fuel economy improvement function applied to the hybrid control unit (HCU) of the Hyundai Santa Fe. This function uses the gradient and average speed information of the upcoming road to perform optimal driving point control of the engine and motor of the hybrid electric vehicle (HEV) based on the expected required power. The components of the simulation environment are HCU virtual controllers, vehicle models, roads, and navigation. Virtual controllers were created using virtual controller technology based on HCU mass production codes. The vehicle model is a Transmission Mounted Electric Device (TMED) system with the powertrain specifications of a Hyundai Santa Fe Hybrid. Road and navigation information was collected using actual vehicle test data. The consolidation of the simulation environment was confirmed by comparing the actual vehicle test data and simulation data, such as the vehicle model, MPC energy prediction control function and fuel economy model. As a result of the simulation, the characteristics of the MPC energy prediction control were confirmed and the fuel economy improved to similar to that of the vehicle test using a robot driver.