4.7 Article

A novel cascade organic Rankine cycle (ORC) system for waste heat recovery of truck diesel engines

期刊

ENERGY CONVERSION AND MANAGEMENT
卷 138, 期 -, 页码 210-223

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2017.01.056

关键词

Waste heat recovery; Organic Rankine cycle (ORC); Diesel engine; Cascade expansion

资金

  1. National Natural Science Foundation of China [51636005]

向作者/读者索取更多资源

Waste heat recovery (WHR) of engines has attracted increasingly more concerns recently, as it can improve engine thermal efficiency and help truck manufacturers meet the restrictions of CO2 emission. The organic Rankine cycle (ORC) has been considered as the most potential technology of WHR. To take full advantage of waste heat energy, the waste heat in both exhaust gases and the coolant need to be recovered; however, conventional multi-source ORC systems are too complex for vehicle applications. This paper proposed a confluent cascade expansion ORC (CCE-ORC) system for engine waste heat recovery, which has simpler architecture, a smaller volume and higher efficiency compared with conventional dual-loop ORC systems. Cyclopentane is analyzed to be regarded as the most suitable working fluid for this novel system. A thermodynamic simulation method is established for this system, and off-design performance of main components and the working fluid side pressure drop in the condenser have been taken into consideration. System performance simulations under full engine operating conditions are conducted for the application of this system on a heavy-duty truck diesel engine. Results show that the engine peak thermal efficiency can be improved from 45.3% to 49.5% where the brake specific fuel consumption (BSFC) decreases from 185.6 g/(kW h) to 169.9 g/(kW h). The average BSFC in the frequently operating region can decrease by 9.2% from 187.9 g/(kW h) to 172.2 g/(kW h). Compared with the conventional dual-loop ORC system, the CCE-ORC system can generate 8% more net power, while the total volume of heat exchangers is 18% less. (C) 2017 Elsevier Ltd. All rights reserved.

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