INTRODUCTION
Increasing environmental and safety concerns, along with
rising gasoline prices, are driving a worldwide shift in the
automotive industry towards the development of green
intelligent transportation systems. Today, electric vehicles
(EVs) are seen as the leading contender to displace existing
fleets of gasoline-powered cars. EVs allow for the possibility
of zero greenhouse-gas and air-pollutant emissions as well as
very little noise pollution. Another important advantage of
electric vehicles over the conventional internal combustion
engines (ICEs) is the very high energy efficiency and
relatively low cost of the electric motor. The main concern
currently being faced is the low energy and power densities
of batteries compared to the liquid fuels.
EVs use electric motors to propel the car and use batteries
to store electricity. Four in-wheel motors, two independentmotors for the front and rear axles, and a single motor
running all four wheels are possible motor configurations for
shaping the propel system. The rapid dynamics of the motors
provide the opportunity to accurately control the wheel
speeds, thereby achieving better handling performance. In
addition, this property allows stability and safety controllers
such as active cruise control, collision avoidance, and
emergency brake assist to apply their commands much faster,
resulting in better incident prevention. Motors in EVs also
help in stabilizing vehicle motion by generating counter-
directional torques between the left and right wheels using
control strategies such active software differentials, active
brake bias, and brake steer. While applying these controllers
on ICEVs requires sophisticated hardware components that
add complexity to the vehicle structure, the application of
such controllers in EVs can be carried out using only
software modification.
2013-01-0674
Published 04/08/2013
Copyright © 2013 SAE International
doi:10.4271/2013-01-0674
saecomveh.saejournals.org
Optimal Torque Control for an Electric-Drive Vehicle with In-
Wheel Motors: Implementation and Experiments
Abtin Athari
Univ. of Waterloo
Saber Fallah
Univ. of Surrey
Bin Li and Amir Khajepour
Univ. of Waterloo
Shih-Ken Chen and Baktiar Litkouhi
General Motors Company
ABSTRACT
This paper presents the implementation of an off-line optimized torque vectoring controller on an electric-drive vehicle
with four in-wheel motors for driver assistance and handling performance enhancement. The controller takes vehicle
longitudinal, lateral, and yaw acceleration signals as feedback using the concept of state-derivative feedback control. The
objective of the controller is to optimally control the vehicle motion according to the driver commands. Reference signals
are first calculated using a driver command interpreter to accurately interpret what the driver intends for the vehicle
motion. The controller then adjusts the braking/throttle outputs based on discrepancy between the vehicle response and the
interpreter command. A test vehicle equipped with four in-wheel electric motors, vehicle sensors, communication buses,
and dSPACE rapid prototyping hardware is instrumented and the control performance is verified through vehicle handling
tests under different driving conditions.
CITATION: Athari, A., Fallah, S., Li, B., Khajepour, A. et al., "Optimal Torque Control for an Electric-Drive Vehicle with
In-Wheel Motors: Implementation and Experiments," SAE Int. J. Commer. Veh. 6(1):2013, doi:10.4271/2013-01-0674.
____________________________________
82Downloaded from SAE International by Univ of California, Tuesday, July 31, 2018Substantial research has been carried out on the
development of electric
vehicles and related control strategies
during the last two decades. For example, Ref. [ 1] provides
an overview
of electric-vehicle technology while Refs. [ 2]
and [ 3] report on the application of different stability
controllers in
electric vehicles. Moreover, a combination of
direct yaw-moment and act
SAE_2013-01-0674_Optimal Torque Control for an Electric-Drive Vehicle with In- Implementation and Experiments
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