Thermodynamic analysis and parametric optimization of a novel S–CO2 power cycle for the waste heat recovery of internal combustion engines. (15th October 2020)

• Record Type: Journal Article
• Authors: Zhang, Ruiyuan; Su, Wen; Lin, Xinxing; Zhou, Naijun; Zhao, Li
• Is Part Of: Energy. Volume 209(2020)
• Publication Date: 2020-10-15
• Subjects: Supercritical carbon dioxide -- Brayton cycle -- Waster heat recovery -- Thermodynamic analysis -- GA optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.118484
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: With the aim to recover the exhaust heat of internal combustion engine efficiently, a novel supercritical CO2 (S–CO2 ) power cycle is proposed on the basis of recompression cycle configuration. The corresponding thermodynamic models are established to analyze the energetic and exergetic performances of the system. The effects of turbine inlet temperatures and system pressures are investigated. Thereafter, in order to output the maximum net work, genetic algorithm (GA) is employed to optimize these key parameters. Under design conditions, the calculated results indicate that the thermal efficiency and the exergy efficiency of the system can reach up to 35.86% and 67.90% respectively. Furthermore, as the inlet temperature of high pressure turbine increases, cycle efficiency increases while output work decreases. However, for the effect of inlet temperature of low pressure turbine, cycle efficiency and output work increase with the increase of temperature. As for the intermediate pressure of this system, there exist pressures to get the maximum net work and cycle efficiency. Based on GA optimization, an optimal combination of system parameters is obtained. The corresponding maximum cycle power is 39.49 kW, and the recovery efficiency of waste heat can reach up to 74.83%. Highlights: A novel S–CO2 system is proposed to efficiently recover the waste heat of ICE. Thermodynamic models and optimization are established for the system. Effects of cycle parameters are comprehensively analyzed.