Range Extension Autonomous Driving for Electric Vehicles Based on Optimal Velocity Trajectory Generation and Front-Rear Driving-Braking Force Distribution

Abstract

Electric vehicles (EVs) have been intensively studied over the past decade, owing to their environmentally-friendly characteristics. However, the miles-per-charge of typical EVs is lower than the cruising range of typical internal combustion engine vehicles. To increase miles-per-charge, the authors' research group has proposed a series of control systems, including Range Extension Control Systems (RECS) and Range Extension Autonomous Driving (READ) systems. In this paper, by considering the load transfer, slip ratio, motor losses, a READ system is proposed that optimizes the velocity trajectory and the front and rear driving-braking force distribution ratio; these techniques help reduce the consumption energy of the autonomous vehicle. The effectiveness of the proposed method is verified by simulations and experiments.

Iterative Dynamic Programming for Optimal Control Problem with Isoperimetric Constraint and Its Application to Optimal Eco-driving Control of Electric Vehicle

“…For EV, whose battery capacity is limited, the effective use of energy by reducing its energy consumption also solves the problem of short mileage per charge (1) (2) . For example, range extension control system (RECS) (1) (2) is proposed to extend the cruising range of a vehicle by motion control. They assumed that an EV has more than one motor and that suitable torque distribution results in improved efficiency.…”

Range Extension Autonomous Driving for Electric Vehicle Based on Optimal Vehicle Velocity Profile in Consideration of Cornering

“…It is thought that autonomous driving technology will continue to be adopted with the evolution of ITS, and that the authority over vehicle velocity will be transferred from the driver to the ITS. Our group of authors has also published research on range extension autonomous driving (READ) in which range is extended by minimizing energy consumption by optimizing the velocity trajectory based on a detailed motion/power consumption model [9,10]. Reference [8] attempts to reduce energy consumption by predicting the behavior of a leading vehicle and considering traffic light information to determine the optimal control input based on model predictive control of an internal combustion vehicle.…”

“…Reference [8] attempts to reduce energy consumption by predicting the behavior of a leading vehicle and considering traffic light information to determine the optimal control input based on model predictive control of an internal combustion vehicle. Our group of authors has also published research on range extension autonomous driving (READ) in which range is extended by minimizing energy consumption by optimizing the velocity trajectory based on a detailed motion/power consumption model [9,10]. Note that, in these studies, we assumed that road information and signal information such as gradient can be acquired from the ITS.…”

Range Extension Control of a Three-Wheel Electric Vehicle Prototype Based on Aggregation and Distribution

“…The key idea of RECS is to find the driving distribution ratios that minimizes the summation of the output powers, the copper losses, and the iron losses (7) . The effectiveness of this idea has been verified through the history of RECS (7) (8) (9) (10) . Literature review also shows several concepts which shared the common philosophy with RECS.…”

“…To mention just a few examples, we have anti-slip control (1) (2) , slip ratio control (3) (4) , and driving force control (5) (6) . Recently, range extension control system (RECS) has been shown a great success (7) (8) (9) (10) . The key idea of RECS is to find the driving distribution ratios that minimizes the summation of the output powers, the copper losses, and the iron losses (7) .…”