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Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems

Author

Listed:
  • Ivan Cvok

    (Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia)

  • Igor Ratković

    (Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia)

  • Joško Deur

    (Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, 10000 Zagreb, Croatia)

Abstract

The heating, ventilation and air conditioning (HVAC) system negatively affects the electric vehicle (EV) driving range, especially under cold ambient conditions. Modern HVAC systems based on the vapour-compression cycle can be rearranged to operate in the heat pump mode to improve the overall system efficiency compared to conventional electrical/resistive heaters. Since such an HVAC system is typically equipped with multiple actuators (compressor, pumps, fans, valves), with the majority of them being controlled in open loop, an optimisation-based control input allocation is necessary to achieve the highest efficiency. This paper presents a genetic algorithm optimisation-based HVAC control input allocation method, which utilises a multi-physical HVAC system model implemented in Dymola/Modelica. The considered control inputs include the cabin inlet air temperature reference, blower and radiator fan air mass flows and secondary coolant loop pumps’ speeds. The optimal allocation is subject to specified, target cabin air temperatures and heating power. Additional constraints include actuator hardware limits and safety functions, such as maintaining the superheat temperature at its reference level. The optimisation objective is to maximise the system efficiency defined by the coefficient of performance (COP). The optimised allocation maps are fitted by proper mathematical functions to facilitate the control strategy implementation and calibration. The overall control strategy consists of superimposed cabin air temperature controller that commands heating power, control input allocation functions, and low-level controllers that ensure cabin inlet air and superheat temperature regulation. The control system performance is verified through Dymola simulations for the heat pump mode in a heat-up scenario. Control input allocation map optimisation results are presented for air-conditioning (A/C) mode, as well.

Suggested Citation

  • Ivan Cvok & Igor Ratković & Joško Deur, 2020. "Optimisation of Control Input Allocation Maps for Electric Vehicle Heat Pump-based Cabin Heating Systems," Energies, MDPI, vol. 13(19), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5131-:d:422926
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    References listed on IDEAS

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    1. Myeong Hyeon Park & Sung Chul Kim, 2017. "Heating Performance Characteristics of High-Voltage PTC Heater for an Electric Vehicle," Energies, MDPI, vol. 10(10), pages 1-14, September.
    2. Daniele Basciotti & Dominik Dvorak & Imre Gellai, 2020. "A Novel Methodology for Evaluating the Impact of Energy Efficiency Measures on the Cabin Thermal Comfort of Electric Vehicles," Energies, MDPI, vol. 13(15), pages 1-16, July.
    3. Qinghong Peng & Qungui Du, 2016. "Progress in Heat Pump Air Conditioning Systems for Electric Vehicles—A Review," Energies, MDPI, vol. 9(4), pages 1-17, March.
    4. Zhang, Zhenying & Wang, Jiayu & Feng, Xu & Chang, Li & Chen, Yanhua & Wang, Xingguo, 2018. "The solutions to electric vehicle air conditioning systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 443-463.
    5. Qi, Zhaogang, 2014. "Advances on air conditioning and heat pump system in electric vehicles – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 754-764.
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    Cited by:

    1. Zhang, Nan & Lu, Yiji & Ouderji, Zahra Hajabdollahi & Yu, Zhibin, 2023. "Review of heat pump integrated energy systems for future zero-emission vehicles," Energy, Elsevier, vol. 273(C).
    2. Ivan Panfilov & Alexey N. Beskopylny & Besarion Meskhi, 2024. "Improving the Fuel Economy and Energy Efficiency of Train Cab Climate Systems, Considering Air Recirculation Modes," Energies, MDPI, vol. 17(9), pages 1-26, May.
    3. Gian Luca Patrone & Elena Paffumi & Marcos Otura & Mario Centurelli & Christian Ferrarese & Steffen Jahn & Andreas Brenner & Bernd Thieringer & Daniel Braun & Thomas Hoffmann, 2022. "Assessing the Energy Consumption and Driving Range of the QUIET Project Demonstrator Vehicle," Energies, MDPI, vol. 15(4), pages 1-21, February.
    4. Ivan Cvok & Igor Ratković & Joško Deur, 2021. "Multi-Objective Optimisation-Based Design of an Electric Vehicle Cabin Heating Control System for Improved Thermal Comfort and Driving Range," Energies, MDPI, vol. 14(4), pages 1-24, February.

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