Browse Publications Technical Papers 2018-01-0780

Feasibility Analysis of a Non-Intrusive Exhaust Energy Recovery System Based on the Use of Thermoelectrics 2018-01-0780

This paper presents a feasibility analysis of the use of a thermoelectric generator for the design of a non-intrusive exhaust energy recovery system. The energy recovery system is intended to be used on a light duty vehicle with naturally aspirated internal combustion engine. The non-intrusive characteristic is proposed as an exploratory work with the aim to develop an aftermarket system. The energy source for the system is the exhaust pipe wasted heat. The analysis includes as design variables the number of thermoelectric modules and their location along the exhaust system. The characteristics under analysis are fuel consumption and payload. A numerical model is developed and used to investigate the possible design scenarios. This model is composed by three sub-models. The sub models are mean value engine model, exhaust heat transfer model, and vehicle longitudinal dynamics model. Three driving cycles are used: two standard driving cycles and a real driving cycle. Two commercial technologies were evaluated, but showed negative impact on fuel consumption. Therefore, a third technology, a state of the art technology was considered with the objective to explore possible future capabilities of a high efficiency device. From the feasibility analysis, a fuel consumption reduction potential of 14% is identified for the best case scenario and 10.7% on average. In addition, the highest performance technology showed 0.8% fuel consumption reduction in the best case and 0.67% on average. From the results obtained, it was concluded that the non-intrusive thermoelectric generator is not feasible for the scenarios studied. However, state of the art technology shows capability to reach the potential fuel consumption reduction under certain vehicle operation conditions. Recommendations are given with the aim to attain higher fuel consumption reduction, refinement of models and achieve a feasible system.


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