A Model Reference Adaptive Controller for an Electric Motor Thermal
Management System in Autonomous Vehicles 14-12-01-0001
This also appears in
SAE International Journal of Electrified Vehicles-V132-14EJ
Technological advancements and growth in electric motors and battery packs enable
vehicle propulsion electrifications, which minimize the need for fossil fuel
consumption. The mobility shift to electric motors creates a demand for an
efficient electric motor thermal management system that can accommodate heat
dissipation needs with minimum power requirements and noise generation. This
study proposes an intelligent hybrid cooling system that includes a
gravity-aided passive cooling solution coupled with a smart supplementary liquid
cooling system. The active cooling system contains a radiator, heat sink,
variable frequency drive, alternating current (AC) fan, direct current (DC)
pump, and real-time controller. A complete nonlinear mathematical model is
developed using a lumped parameter approach to estimate the optimum fan and pump
operations at each control interval. Four different control strategies,
including nonlinear model predictive controller, classical proportional-integral
(PI) control, sliding mode control (SMC), and stateflow (SF), are developed, and
their performance is compared. The experimental results demonstrate that the
nonlinear model predictive control (NMPC) method is the most effective strategy,
which reduces the cooling system fan power consumption by 73% for only a 5%
increase in the pump power usage compared to classical PI control for a specific
60-minute driving cycle.
Citation: Shoai Naini, S., Miller, R., Rizoo, D., and Wagner, J., "A Model Reference Adaptive Controller for an Electric Motor Thermal Management System in Autonomous Vehicles," SAE Int. J. Elec. Veh. 12(1):3-16, 2023, https://doi.org/10.4271/14-12-01-0001. Download Citation
Author(s):
Shervin Shoai Naini, Richard Steven Miller, Denise Rizoo, John Wagner
Affiliated:
Clemson University, Department of Mechanical Engineering, USA, US Army CCDC - GVSC, USA
Pages: 14
ISSN:
2691-3747
e-ISSN:
2691-3755
Related Topics:
Electric motors
Mathematical models
Battery packs
Fans
Thermal management
Autonomous vehicles
Fuel consumption
Radiators
Adaptive control
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