Nonlinear Model Predictive Speed Control of Electric Vehicles Represented by Linear Parameter Varying Models with Bias terms

Navid Vafamand, Mohammad Mehdi Arefi, Mohammad Hassan Khooban, Tomislav Dragicevic, Frede Blaabjerg

Research output: Contribution to journalJournal articleResearchpeer-review

5 Citations (Scopus)
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Abstract

This paper investigates a novel approach to design a nonlinear optimal model predictive controller for the speed control of constrained nonlinear electric vehicles (EVs). The proposed approach employs a linear parameter varying model including bias terms and a model predictive scheme. The controller design conditions are derived in terms of linear matrix inequalities (LMIs), which can be solved through convex optimization techniques. Due to considering bias terms in the system dynamic, the proposed approach can be regarded as the general case of the existing results. Furthermore, practical limitations on the amplitude of the input signal are considered and formulated in terms of LMIs. An EV dynamic with bias term is presented and hardware-in-the-loop real time and experiments are carried out to illustrate the effectiveness and merits of the proposed approach over the existing results.
Original languageEnglish
Article number8554296
JournalIEEE Journal of Emerging and Selected Topics in Power Electronics
Volume7
Issue number3
Pages (from-to)2081 - 2089
Number of pages9
ISSN2168-6777
DOIs
Publication statusPublished - Sep 2019

Fingerprint

Speed control
Electric vehicles
Linear matrix inequalities
Controllers
Convex optimization
Dynamical systems
Hardware
Experiments

Keywords

  • DC motors
  • Electric vehicles
  • Linear matrix inequality (LMI)
  • Linear parameter varying (LPV)
  • Nonlinear light-weighted electric vehicle
  • Nonlinear model predictive control
  • Power electronics
  • Practical constraint
  • Predictive control
  • Predictive models
  • Vehicle dynamics
  • Velocity control
  • linear parameter varying (LPV)
  • nonlinear model predictive control (NMPC)
  • nonlinear light-weighted electric vehicle (LWEV)
  • practical constraint

Cite this

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title = "Nonlinear Model Predictive Speed Control of Electric Vehicles Represented by Linear Parameter Varying Models with Bias terms",
abstract = "This paper investigates a novel approach to design a nonlinear optimal model predictive controller for the speed control of constrained nonlinear electric vehicles (EVs). The proposed approach employs a linear parameter varying model including bias terms and a model predictive scheme. The controller design conditions are derived in terms of linear matrix inequalities (LMIs), which can be solved through convex optimization techniques. Due to considering bias terms in the system dynamic, the proposed approach can be regarded as the general case of the existing results. Furthermore, practical limitations on the amplitude of the input signal are considered and formulated in terms of LMIs. An EV dynamic with bias term is presented and hardware-in-the-loop real time and experiments are carried out to illustrate the effectiveness and merits of the proposed approach over the existing results.",
keywords = "DC motors, Electric vehicles, Linear matrix inequality (LMI), Linear parameter varying (LPV), Nonlinear light-weighted electric vehicle, Nonlinear model predictive control, Power electronics, Practical constraint, Predictive control, Predictive models, Vehicle dynamics, Velocity control, linear parameter varying (LPV), nonlinear model predictive control (NMPC), nonlinear light-weighted electric vehicle (LWEV), practical constraint",
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Nonlinear Model Predictive Speed Control of Electric Vehicles Represented by Linear Parameter Varying Models with Bias terms. / Vafamand, Navid; Arefi, Mohammad Mehdi; Khooban, Mohammad Hassan; Dragicevic, Tomislav; Blaabjerg, Frede.

In: IEEE Journal of Emerging and Selected Topics in Power Electronics, Vol. 7, No. 3, 8554296, 09.2019, p. 2081 - 2089.

Research output: Contribution to journalJournal articleResearchpeer-review

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