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Optimization of Control Parameters of Vehicle Air-Conditioning System for Maximum Efficiency
Technical Paper
2020-01-1242
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Modern automotive heating, ventilation, and air-conditioning (HVAC) systems have multiple and often redundant actuators. Design of a control system that optimally synthesizes multiple control actions while satisfying control set points and system hardware-related constraints is necessary to maximize HVAC efficiency. To this end, an optimization approach to control system design is proposed in this paper and demonstrated for a generic air-conditioning (A/C) system. The paper first outlines a nonlinear 12th-order A/C dynamics model based on the moving-boundary method. Then, the A/C control system is defined, which combines feedback controllers commanding the compressor speed and expansion valve opening, and open-loop actions of condenser and blower fans. Next, a three-stage, multi-objective genetic algorithm-based approach of control system optimization is proposed. The first-stage is aimed at finding a rough estimate of all control inputs, which maximizes the A/C system efficiency while satisfying relaxed control set point constraints. In the second stage, the closed-loop controller parameters are optimized for the operating point obtained in the first stage with the aim to provide a favorable trade-off between the control error suppression and control effort. The third stage includes refined optimization of fans open-loop actions to maximize efficiency, where firmer thermal comfort and safety-related constraints are provided by feedback controllers. Finally, the optimization procedure is carried out for multiple control set points to provide control parameter maps, which are aimed to be used in the form of a gain-scheduling algorithm. Analysis of optimization computational efficiency shows that a substantial improvement is achieved with the proposed, comprehensive three-stage approach when compared to using only the first stage one.
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Cvok, I., Ratkovic, I., and Deur, J., "Optimization of Control Parameters of Vehicle Air-Conditioning System for Maximum Efficiency," SAE Technical Paper 2020-01-1242, 2020, https://doi.org/10.4271/2020-01-1242.Also In
References
- Zhang , T. , Gao , C. , Gao , Q. , Wang , G. et al. Status and Development of Electric Vehicle Integrated Thermal Management from BTM to HVAC Appl. Therm. Eng. 88 398 409 2015 10.1016/j.applthermaleng.2015.02.001
- Paffumi , E. , Otura , M. , Centurelli , M. , Casellas , R. et al. Energy Consumption, Driving Range and Cabin Temperature Performances at Different Ambient Conditions in Support to the Design of a User-Centric Efficient Electric Vehicle: The QUIET Project 14th SDEWES Conference Dubrovnik 2019
- Zhang , Z. , Wang , J. , Feng , X. , Chang , L. et al. The Solutions to Electric Vehicle Air Conditioning Systems: A Review Renew. Sustain. Energy Rev. 91 443 463 2018 10.1016/j.rser.2018.04.005
- Drage , P. , Hinteregger , M. , Zotter , G. , and Šimek , M. Cabin Conditioning for Electric Vehicles ATZ Worldwide 121 2 44 49 2019 10.1007/s38311-018-0209-2
- Khayyam , H. , Kouzani , A. , Hu , E. , and Nahavandi , S. Coordinated Energy Management of Vehicle Air Conditioning System Appl. Therm. Eng. 31 5 750 764 2011 10.1016/j.applthermaleng.2010.10.022
- Amini , M.R. , Wang , H. , Gong , X. , Liao-McPherson , D. et al. Cabin and Battery Thermal Management of Connected and Automated HEVs for Improved Energy Efficiency Using Hierarchical Model Predictive Control IEEE Trans. Control Syst. Technol. 1 16 2019 10.1109/tcst.2019.2923792
- Cvok , I. , Škugor , B. , and Deur , J. Control Trajectory Optimisation and Optimised Control Strategy for an Electric Vehicle HVAC System and Favourable Thermal Comfort 14th SDEWES Conference Dubrovnik 2019
- Zhang , Q. , Meng , Y. , Greiner , C. , Soto , C. et al. Air Conditioning System Performance and Vehicle Fuel Economy Trade-Offs for a Hybrid Electric Vehicle SAE Technical Paper 2017-01-0171 2017 https://doi.org/10.4271/2017-01-0171
- Jensen , J.M. and Tummerscheit , H. Moving Boundary Models for Dynamics Simulations of Two-Phase Flows 2nd Int. Model. Conf. 2002 235 244
- Ratković , I. , Cvok , I. , Soldo , V. , and Deur , J. Control Oriented Modelling of Vapour-Compression Cycle Including Model-order Reduction and Analysis Tools 14th SDEWES Conference Dubrovnik 2019
- Isermann , R. Digital Control Systems Berlin Springer-Verlag 1981
- Poles , S. 2003