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The conventional air conditioning system used in high-speed railways has limitations in heating performance and environmental impact, necessitating the exploration of alternative refrigerants. The transcritical CO 2 system has gained popularity due to its exceptional heating efficiency and environmental benefits. This study aims to evaluate the energy and environmental potentials for transcritical CO 2 systems in high-speed trains based on four-vertical-and-four-horizontal railway lines within different climatic regions of China. A high-fidelity transcritical CO 2 system model was first developed and validated through experiments. Then, a comprehensive energy and environmental evaluation method was proposed and applied to the four-vertical-and-four-horizontal railway lines. The results indicated that the transcritical CO 2 system had a superior heating performance and competitive cooling performance based on daily and annual operations. Furthermore, the transcritical CO 2 system exhibited significant environmental advantages with lower total life cycle climate performance for all lines, with an average emissions reduction ratio of 17.6% and a maximum emissions reduction ratio of 26.98%. These findings highlight the competitive energy performance and outstanding environmental benefits offered by transcritical CO 2 systems as promising alternatives to air conditioning systems in railway transportation. • This paper evaluates the potential of theCO 2 system in high-speed trains from an energy performance and environmental benefits perspective. • A high-fidelity model of the transcritical CO 2 system is developed and validated for effectiveness through experiments. • The energy and environmental evaluations are conducted based on China's four-vertical-and- four-horizontal railway lines. • The results indicate that the CO 2 system presents a competitive alternative for air conditioning systems in high-speed trains. [ABSTRACT FROM AUTHOR]

The thermal management system (TMS) in electric vehicles (EVs) is a comprehensive system that integrates an air conditioning system for the cabin, a temperature control system for the battery, and a cooling system for the motor. The currently used PI control strategy can only meet the basic TMS functions and cause high energy consumption. In this paper, we present a novel model predictive control (MPC) strategy for the TMS to optimize operational performance in real time. Different from the independent PI control for the individual components, MPC can predict future operation conditions and provide the optimal operating inputs in advance. A complete control-oriented model for MPC is developed, and the MPC strategy is designed to minimize the total power consumption of the TMS under the control-oriented model and constraints. The evaluation is carried out under several cases including the fixed ambient temperature, realistic ambient temperature, and different vehicle speeds. The results showed that the novel MPC strategy saved energy consumption by 5.9%–10.3% in these cases when compared to the PI strategy, demonstrating the effectiveness and feasibility of the proposed MPC control. • Proposed a model predictive control strategy for thermal management systems in EVs. • Developed a control-oriented model based on data-driven methods and physical principles. • Minimizes total power consumption while maintaining cabin and battery temperatures. • Results demonstrate the effectiveness of the MPC strategy under various conditions. [ABSTRACT FROM AUTHOR]