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GLOS, J. OTAVA, L. VÁCLAVEK, P.
Original Title
Non-Linear Model Predictive Control of Cabin Temperature and Air Quality in Fully Electric Vehicles
Type
journal article in Web of Science
Language
English
Original Abstract
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.
Keywords
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
Authors
GLOS, J.; OTAVA, L.; VÁCLAVEK, P.
Released
25. 1. 2021
Publisher
IEEE
Location
PISCATAWAY
ISBN
0018-9545
Periodical
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Year of study
70
Number
2
State
United States of America
Pages from
1216
Pages to
1229
Pages count
14
URL
https://ieeexplore.ieee.org/document/9335535
Full text in the Digital Library
http://hdl.handle.net/11012/196512
BibTex
@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" }