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Abstract A turbulent combustion test platform is designed. It is demonstrated that the turbulent environment in a constant volume combustion chamber is isotropic and controllable. Based on the platform, the turbulent combustion characteristics of methane/air are studied. The collected flame image and combustion pressure data are analysed. The results show that when the initial temperature is 300 K, the initial pressure is 1 bar, and the equivalence ratio is ϕ = 1 , the flame shape maintains self-similarity in the propagation process under different turbulence intensities. With the increase in turbulence intensity, there are more cracks on the flame surface and more wrinkles on the flame front; with the increase in turbulence intensity, the combustion propagation rate increases, the flame propagation rate increases at the same flame radius, and the maximum combustion pressure and the rate of pressure rise increase. When the turbulence intensity is constant, the test results of equivalence ratios of 0.8, 1.0 and 1.2 are compared. At an equivalent ratio of 1, the flame propagation rate and the stretch rate of the flame are maximized, and the maximum burning pressure and pressure rise rate are maximized.

Abstract A turbulent combustion test platform is designed. It is demonstrated that the turbulent environment in a constant volume combustion chamber is isotropic and controllable. Based on the platform, the turbulent combustion characteristics of methane/air are studied. The collected flame image and combustion pressure data are analysed. The results show that when the initial temperature is 300 K, the initial pressure is 1 bar, and the equivalence ratio is ϕ = 1 , the flame shape maintains self-similarity in the propagation process under different turbulence intensities. With the increase in turbulence intensity, there are more cracks on the flame surface and more wrinkles on the flame front; with the increase in turbulence intensity, the combustion propagation rate increases, the flame propagation rate increases at the same flame radius, and the maximum combustion pressure and the rate of pressure rise increase. When the turbulence intensity is constant, the test results of equivalence ratios of 0.8, 1.0 and 1.2 are compared. At an equivalent ratio of 1, the flame propagation rate and the stretch rate of the flame are maximized, and the maximum burning pressure and pressure rise rate are maximized.

Abstract This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.

Abstract This paper studies the optimization of a small-scale central air-conditioning system, in which the cooling is provided by a ground source heat pump (GSHP) equipped with an on/off capacity control. The optimization strategy aims to optimize the overall system energy consumption and simultaneously guarantee the robustness of the space air temperature control without violating the allowed GSHP maximum start-ups number per hour specified by customers. The set-point of the chilled water return temperature and the width of the water temperature control band are used as the decision variables for the optimization. The performance of the proposed strategy was tested on a simulation platform. Results show that the optimization strategy can save the energy consumption by 9.59% in a typical spring day and 2.97% in a typical summer day. Meanwhile it is able to enhance the space air temperature control robustness when compared with a basic control strategy without optimization.

Abstract A novel combined cooling and power (CCP) system integrating a supercritical carbon dioxide recompression Brayton cycle with an ejector transcritical carbon dioxide refrigeration cycle (E-TCRC) is proposed to realize the effective utilization of nuclear power. In the proposed system, a portion of CO2 exiting the pre-cooler is used to drive the E-TCRC for generating cooling and recovering partial waste heat of sCO2 turbine exhaust. The mathematical model and economic model of the proposed system are established under steady-state conditions. Besides, the exergy efficiency and total product unit cost of the system are selected as the main criteria to evaluate system performance. Parametric analysis is applied to study the effects of four key parameters on the system performance. The CCP system, conventional separated cooling and power (C-SCP) system and ejector separated cooling and power (E-SCP) system are optimized by single-objective and multi-objective optimization. Single-objective optimization reveals that the exergy efficiencies of the CCP system are up to 1.08%pt (percentage point), 0.80%pt and 0.47%pt higher than those of the C-SCP system at the corresponding evaporation temperatures (−20 °C, −10 °C and 0 °C). Besides, the CCP system performs better than the E-SCP system at lower turbine inlet pressures. The multi-objective optimization shows that when the evaporation temperature increases from −20 °C to 0 °C, the total product unit cost of the CCP system decreases from 10.087 $/GJ to 9.668 $/GJ, and exergy efficiency increases from 59.25% to 60.97%.

Abstract A novel combined cooling and power (CCP) system integrating a supercritical carbon dioxide recompression Brayton cycle with an ejector transcritical carbon dioxide refrigeration cycle (E-TCRC) is proposed to realize the effective utilization of nuclear power. In the proposed system, a portion of CO2 exiting the pre-cooler is used to drive the E-TCRC for generating cooling and recovering partial waste heat of sCO2 turbine exhaust. The mathematical model and economic model of the proposed system are established under steady-state conditions. Besides, the exergy efficiency and total product unit cost of the system are selected as the main criteria to evaluate system performance. Parametric analysis is applied to study the effects of four key parameters on the system performance. The CCP system, conventional separated cooling and power (C-SCP) system and ejector separated cooling and power (E-SCP) system are optimized by single-objective and multi-objective optimization. Single-objective optimization reveals that the exergy efficiencies of the CCP system are up to 1.08%pt (percentage point), 0.80%pt and 0.47%pt higher than those of the C-SCP system at the corresponding evaporation temperatures (−20 °C, −10 °C and 0 °C). Besides, the CCP system performs better than the E-SCP system at lower turbine inlet pressures. The multi-objective optimization shows that when the evaporation temperature increases from −20 °C to 0 °C, the total product unit cost of the CCP system decreases from 10.087 $/GJ to 9.668 $/GJ, and exergy efficiency increases from 59.25% to 60.97%.

Abstract The powertrain system of a typical proton electrolyte membrane hybrid fuel cell vehicle contains a lithium battery package and a fuel cell stack. A multi-objective optimization for this powertrain system of a passenger car, taking account of fuel economy and system durability, is discussed in this paper. Based on an analysis of the optimum results obtained by dynamic programming, a soft-run strategy was proposed for real-time and multi-objective control algorithm design. The soft-run strategy was optimized by taking lithium battery size into consideration, and implemented using two real-time algorithms. When compared with the optimized dynamic programming results, the power demand-based control method proved more suitable for powertrain systems equipped with larger capacity batteries, while the state of charge based control method proved superior in other cases. On this basis, the life cycle cost was optimized by considering both lithium battery size and equivalent hydrogen consumption. The battery capacity selection proved more flexible, when powertrain systems are equipped with larger capacity batteries. Finally, the algorithm has been validated in a fuel cell city bus. It gets a good balance of fuel economy and system durability in a three months demonstration operation.