The Effect of Driver's Behavior and Environmental Conditions on Thermal Management of Electric Vehicles

Kim, Jaewoong; Rodríguez, Rodolfo; Kwak, Kyoung Hyun; Jung, Dohoy; Kim, Youngki

doi:10.4271/2020-01-1382

Cited by 5 publications

(12 citation statements)

References 17 publications

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“…The proposed LTV‐MPC controller is implemented in a high‐fidelity MATLAB/Simulink ® plant model 11,25 for vehicle simulations. The LTV‐MPC problem is solved by using qpOASES 26 in the form of QP shown in Equation ().…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…In this subsection, the performance of the LTV‐MPC controller with selected weighting factors from the parametric studies is evaluated under four driving cycles: the UDDS, the HWFET, and the US06, which are used in the parametric study to determine the optimal set of weighting factors, and the WLTC cycle, which is used for performance validation. Particularly, the LTV‐MPC is compared with the NEMPC 17 and the RB controller 11 from our previous works. These two controllers are also implemented in the MATLAB/Simulink ® high‐fidelity plant model.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…For vehicle cabin climate control, various control techniques have been introduced in the literature. A rule‐based (RB) controller typically utilizes map‐based control actions depending on given environmental conditions and various states as measured from the heating, ventilation, and air conditioning (HVAC) system of the vehicle cabin 11 . The maps or rules for the control actions need to be pre‐calibrated for given driving conditions and operating ranges.…”

Section: Introductionmentioning

confidence: 99%

“…The performance of the proposed LTV‐MPC controller is evaluated under a validation driving cycle. The evaluation results are compared with the NEMPC and the RB controller 11 . Finally, concluding remarks and discussion on future directions are given in Section 5.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Energy‐efficient cabin climate control of electric vehicles using linear time‐varying model predictive control

Chen

Kwak

Kim

et al. 2021

Optim Control Appl Methods

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A cabin climate control system, often referred to as a heating, ventilation, and air conditioning (HVAC) system, is one of the largest auxiliary loads of an electric vehicle (EV), and the real-time optimal control of HVAC brings a significant energy-saving potential. In this article, a linear-time-varying (LTV) model predictive control (MPC)-based approach is presented for energy-efficient cabin climate control of EVs. A modification is made to the cost function in the considered MPC problem to simplify the Hessian matrix in utilizing quadratic programming for real-time computation. A rigorous parametric study is conducted to determine optimal weighting factors that work robustly under various operating conditions. Then, the performance of the proposed LTV-MPC controller is compared against a rule-based (RB) controller and a nonlinear economic MPC (NEMPC) benchmark. Compared with the RB controller benchmark, the LTV-MPC reaches the target cabin temperature at least 69 s faster with 3.2% to 15% less HVAC system energy consumption, and the averaged cabin temperature difference is 0.7 • C at most. Compared with the NEMPC, the LTV-MPC controller can achieve comparable performance in temperature regulation and energy consumption with fast computation time: the maximum differences in temperature and energy consumption are 0.4 • C and 2.6%, respectively, and the computational time is reduced 72.4% on average with the LTV-MPC.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy‐efficient cabin climate control of electric vehicles using linear time‐varying model predictive control

Chen

Kwak

Kim

et al. 2021

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

show abstract

“…Wang [5] established a thermal management model for fuel cell vehicles, and studied the influence of different fan selection and operating conditions. Kim et al [6] carried out the influence of the driver's acceleration behavior and environmental conditions on the thermal management of electric vehicles. Pu [7] analysed the flow, pressure and heat related influence of the thermal management system, and put forward suggestions for system structure design and optimization.…”

Section: Introductionmentioning

confidence: 99%

Research on Thermal Balance Test and Evaluation Technology of Fuel Cell Vehicle

Guo

Liang

et al. 2022

J. Phys.: Conf. Ser.

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Thermal management system is importance to the efficiency and durability of fuel cell vehicles, so related researches are carried out on the thermal balance test and evaluation of fuel cells. Through theoretical and technical analysis, a test and evaluation method of thermal management system applied to various extreme conditions is proposed, and the test and evaluation conditions and evaluation indicators of each system of fuel cell vehicles are formed. In this paper, the thermal balance test results of a fuel cell vehicle are analyzed. The research results show that the thermal balance of fuel cell vehicles under extreme conditions reduces power and increases temperature difference to dissipate heat

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Thermal comfort-conscious eco-climate control for electric vehicles using model predictive control

Kwak

Chen

Kim³

et al. 2023

Control Engineering Practice

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The Effect of Driver's Behavior and Environmental Conditions on Thermal Management of Electric Vehicles

Cited by 5 publications

References 17 publications

Energy‐efficient cabin climate control of electric vehicles using linear time‐varying model predictive control

Energy‐efficient cabin climate control of electric vehicles using linear time‐varying model predictive control

Research on Thermal Balance Test and Evaluation Technology of Fuel Cell Vehicle

Thermal comfort-conscious eco-climate control for electric vehicles using model predictive control

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