Maximum Specific Cycle Net-Work Based Performance Analyses and Optimizations of Thermodynamic Gas Power Cycles

34 Pages Posted: 27 Dec 2021

See all articles by Di He

Di He

Beijing Jiaotong University

Yusong Yu

Beijing Jiaotong University

Chaojun Wang

Beijing Jiaotong University

Boshu He

Beijing Jiaotong University

Abstract

A gas power engine is expected to output work or power through cycle, and the work is expected as much as possible in terms of viewpoints of a unit fuel, a unit volume of an engine, or a unit displaced volume of an engine. Specific cycle net-work (SCNW) is defined as the net-work output for 1 kg of working fluid in a cycle. Many Engineering Thermodynamics textbooks focus only on evaluating a gas power engine with thermal efficiency, especially for reciprocating engines, while the important concept of SCNW is ignored which might mislead the engineering applications. Based on the generalized property diagrams for the gas power cycles proposed by the authors, an ideal Otto cycle and an ideal Miller-Diesel cycle are analyzed. The optimum compression ratio (or the pressure ratio) for the maximum SCNW or the maximum mean effective pressure (MEP) is analyzed and optimized. The ideal Otto and the ideal Miller-Diesel cycles, and also other gas power cycles, are concluded that the operation under the condition of maximum SCNW or maximum MEP, instead of that of higher efficiency, is more reasonable and economic.

Keywords: Engineering Thermodynamics, Gas power cycle, Maximum specific cycle net-work (SCNW), Optimum compression/pressure ratio, Generalized property diagrams, Maximum mean effective pressure (MEP)

Suggested Citation

He, Di and Yu, Yusong and Wang, Chaojun and He, Boshu, Maximum Specific Cycle Net-Work Based Performance Analyses and Optimizations of Thermodynamic Gas Power Cycles. Available at SSRN: https://ssrn.com/abstract=3994434 or http://dx.doi.org/10.2139/ssrn.3994434

Di He

Beijing Jiaotong University ( email )

No.3 of Shangyuan Residence Haidian District
Beijing, 100089
China

Yusong Yu

Beijing Jiaotong University ( email )

No.3 of Shangyuan Residence Haidian District
Beijing, 100089
China

Chaojun Wang

Beijing Jiaotong University ( email )

No.3 of Shangyuan Residence Haidian District
Beijing, 100089
China

Boshu He (Contact Author)

Beijing Jiaotong University ( email )

No.3 of Shangyuan Residence Haidian District
Beijing, 100089
China

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