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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. [ABSTRACT FROM AUTHOR]

A spray and evaporation model has been developed and embedded in a quasi-dimensional multi-zone direct injection internal combustion engine simulation framework. The model accounts for the behavior of the spray zone and fuel evaporation including sub-models for spray breakup, improved zone velocity estimations with transient fuel injection, spray penetration and tracking of evaporated fuel components. Each sub-model deals with multi-component fuel surrogates to simulate the real fuel effects. To enhance sensitivity of the model to the fuel components, additional thermophysical properties to the traditional spray model are incorporated. The ideal gas and the ideal solution are assumed in the model to retain computational efficiency. Finally, the model was validated against experiments and compared with other numerical methods. The ability of the new model to treat a multi-component fuel provides an improvement in the simulations of modern direct injection internal combustion engine when used with alternative fuels. [ABSTRACT FROM PUBLISHER]