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Evaluation of Exhaust Heat Recovery System Effectiveness in Engine Friction Reduction and Fuel Economy Improvement for Indian Hatchback
Technical Paper
2017-01-0154
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
With the upcoming regulations for fuel economy and emissions, there is a significant interest among vehicle OEMs and fleet managers in developing computational methodologies to help understand the influence and interactions of various key parameters on Fuel Economy and carbon dioxide emissions. The analysis of the vehicle as a complete system enables designers to understand the local and global effects of various technologies that can be employed for fuel economy and emission improvement. In addition, there is a particular interest in not only quantifying the benefit over standard duty-cycles but also for real world driving conditions.
The present study investigates impact of exhaust heat recovery system (EHRS) on a typical 1.2L naturally aspirated gasoline engine passenger car representative of the India market. Computational Sciences Experts Group (CSEG) has developed a forward calculating Simulink model of the passenger car in order to calculate the engine loading, engine heat rejection and the exhaust energy generated during a drive cycle. The calibrated model was then used to simulate a Modified Indian Drive Cycle (MIDC), and closely integrated with a transient underhood thermal model to evaluate the warm-up impact and the engine friction reduction attributed to the addition of the EHRS system.
This approach can assist in the selection of the appropriate powertrain to optimize fuel economy. Further, the tool and the methodology quantify benefits in real world driving conditions and can help designers make educated investment decisions a cost/benefit and emission impact of the technologies.
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Uppuluri, S., R Khalane, H., and Naiknaware, A., "Evaluation of Exhaust Heat Recovery System Effectiveness in Engine Friction Reduction and Fuel Economy Improvement for Indian Hatchback," SAE Technical Paper 2017-01-0154, 2017, https://doi.org/10.4271/2017-01-0154.Data Sets - Support Documents
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