On Nonlinear Model Predictive Control for Energy-Efficient Torque-Vectoring

A recently growing literature discusses the topics of direct yaw moment control based on model predictive control (MPC), and energy-efficient torque-vectoring (TV) for electric vehicles with multiple powertrains. To reduce energy consumption, the available TV studies focus on the control allocation...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 70; no. 1; pp. 173 - 188
Main Authors: Parra, Alberto, Tavernini, Davide, Gruber, Patrick, Sorniotti, Aldo, Zubizarreta, Asier, Perez, Joshue
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Actuators
Algorithms
Configuration management
control allocation
Cornering
Cost function
Driving conditions
Electric vehicles
Energy conservation
Energy consumption
Energy efficiency
Fuzzy control
Fuzzy logic
Mechanical power transmission
Nonlinear control
nonlinear model predictive control
Optimality criteria
Optimization
Powertrain
powertrain power loss
Predictive control
reference yaw rate
Resource management
tire slip power loss
Tires
Torque
Torque-vectoring
weight adaptation
Wheels
Yawing moments
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:A recently growing literature discusses the topics of direct yaw moment control based on model predictive control (MPC), and energy-efficient torque-vectoring (TV) for electric vehicles with multiple powertrains. To reduce energy consumption, the available TV studies focus on the control allocation layer, which calculates the individual wheel torque levels to generate the total reference longitudinal force and direct yaw moment, specified by higher level algorithms to provide the desired longitudinal and lateral vehicle dynamics. In fact, with a system of redundant actuators, the vehicle-level objectives can be achieved by distributing the individual control actions to minimize an optimality criterion, e.g., based on the reduction of different power loss contributions. However, preliminary simulation and experimental studies - not using MPC - show that further important energy savings are possible through the appropriate design of the reference yaw rate. This paper presents a nonlinear model predictive control (NMPC) implementation for energy-efficient TV, which is based on the concurrent optimization of the reference yaw rate and wheel torque allocation. The NMPC cost function weights are varied through a fuzzy logic algorithm to adaptively prioritize vehicle dynamics or energy efficiency, depending on the driving conditions. The results show that the adaptive NMPC configuration allows stable cornering performance with lower energy consumption than a benchmarking fuzzy logic TV controller using an energy-efficient control allocation layer.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2020.3022022