Experimental investigation and modeling of a reciprocating piston expander for waste heat recovery from a truck engine

Journal article, 2021

Waste heat recovery using an (organic) Rankine cycle has the capacity to significantly increase the efficiency of heavy-duty engines and thereby reduce fuel consumption and CO2 emissions. This paper evaluates a reciprocating piston expander used in a Rankine cycle for truck waste heat recovery by quantifying its performance on the basis of experimental results and simulations. The experimental results were obtained using a setup consisting of a 12.8 L heavy-duty Diesel engine connected to a Rankine cycle with water and are used to calibrate a semi-empirical expander model. At an engine power between 75 and 151 kW, this system recovered between 0.1 and 3 kW, resulting in an expander filling factor between 0.5 and 2.5, and a shaft isentropic effectiveness between 0.05 and 0.5. The calibrated model indicated that the heat loss (16%), mechanical loss (6–25%), pressure drop (13–42%), and leakage (25–75%) all contributed significantly to the expander performance loss. A simulation study with acetone, cyclopentane, ethanol, methanol, and R1233zd(E), showed that a change of working fluid significantly impacts the expander performance, with the filling factor varying between 0.5 and 2.2 and the effectiveness between 0.01 and 0.5, depending on the working fluid, expander speed, and pressure ratio. The results of the optimization of the built-in volume ratio and inlet valve timing during a typical long haul driving cycle showed that acetone and R1233zd(E) provided the highest available power around 3 kW absolute, or 2.2% relative to the engine. The main contributions of this paper are the presentation of experimental results of an engine coupled to a Rankine cycle, and the quantification of performance losses and the effect of working fluid variation using an adapted semi-empirical expander model, which allows for a selection of the working fluid and geometrical modifications giving optimal performance during a long haul driving cycle.