Abstract
This paper presents a terrain-information- and actuator-efficiency- incorporated energy management and driving strategy (EMDS) for maximizing the travel distance of in-wheel motor, pure electric ground vehicles (EGVs). Minimization of energy consumption for a certain trip with terrain preview based on the operating efficiencies of in-wheel motors and a traffic model is essential to maximize the total travel distances of an EGV. Unlike conducting energy optimization under given vehicle speed profiles that are specified a priori in most literature, the optimally varied vehicle velocity and globally optimal in-wheel motor actuation torque distributions are simultaneously obtained to minimize the EGV energy consumption by employing the dynamic programming method for the first time. As a comparison, CarSim-matlab/Simulink co-simulation results based on a model predictive control design are displayed to not only validate that the energy optimization results from the EMDS design is a benchmark with the least power consumption, but also to show that the driving strategy derived from the EMDS can be potentially utilized as an energy-optimal speed reference for other real-time implementable methods.
Original language | English (US) |
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Article number | 6657818 |
Pages (from-to) | 1938-1947 |
Number of pages | 10 |
Journal | IEEE Transactions on Industrial Informatics |
Volume | 10 |
Issue number | 3 |
DOIs | |
State | Published - Aug 2014 |
Externally published | Yes |
Keywords
- Driving strategy
- dynamic programming
- electric ground vehicle (EGV)
- energy management
- in-wheel motor
- model predictive control (MPC)
- terrain preview
ASJC Scopus subject areas
- Control and Systems Engineering
- Information Systems
- Computer Science Applications
- Electrical and Electronic Engineering