Result Details
Non-Linear Model Predictive Control of Cabin Temperature and Air Quality in Fully Electric Vehicles
Otava Lukáš, Ing., Ph.D., RG-2-02 (CEITEC)
Václavek Pavel, prof. Ing., Ph.D., RG-2-02 (CEITEC), UAMT (FEEC)
This article describes an application of Non-linear Model Predictive Control algorithms on energy efficient control of fully electric vehicle cabin temperature and air quality. Since fully electric vehicles can not utilize waste heat from a powertrain (or there is not enough waste heat) as ICE vehicles do, it is necessary to employ advanced control approaches (especially for cabin heating) due to the possible mileage lost by using energy from the batteries for cabin conditioning. The basic idea behind this is to avoid the heat losses caused by excessive air exchange and to ensure a satisfactory air quality in combination with a user defined temperature. The Non-linear Model Predictive control algorithms were successfully implemented into an Infineon AURIX Tricore microcontroller and tested within a Processor in the Loop simulation.
Heating systems; Resistance heating; Waste heat; Atmospheric modeling; Air quality; Heat pumps; Temperature control; Air quality control; battery electric vehicle; extended kalman filter; fully electric vehicle; non-linear model predictive control; temperature control; vehicle cabin model
@article{BUT168057,
author="Jan {Glos} and Lukáš {Otava} and Pavel {Václavek}",
title="Non-Linear Model Predictive Control of Cabin Temperature and Air Quality in Fully Electric Vehicles",
journal="IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY",
year="2021",
volume="70",
number="2",
pages="1216--1229",
doi="10.1109/TVT.2021.3054170",
issn="0018-9545",
url="https://ieeexplore.ieee.org/document/9335535"
}
Department of Control and Instrumentation (UAMT)