This paper describes development of a test cell setup for concurrent running of a real engine and a simulation of the vehicle system, and its use for investigating highly-dynamic engine-in-vehicle operation and its effect on diesel engine emissions. Running an engine in the test cell under conditions experienced in the vehicle enables acquiring detailed insight into dynamic interactions between powertrain sub-systems, and the impact of it on fuel consumption and transient emissions. This type of data may otherwise be difficult and extremely costly to obtain from a vehicle prototype test. In particular, engine system response during critical transients and the effect of transient excursions on emissions are investigated using advanced, fast-response test instrumentation and emissions analyzers. Main enablers of the work include the highly dynamic AC electric dynamometer with the accompanying computerized control system and the computationally efficient simulation of the driveline/vehicle system. The latter is developed through systematic energy-based proper modeling that tailors the virtual model to capture critical powertrain transients while running in real time. Coupling the real engine with the virtual driveline/vehicle offers a chance to easily modify vehicle parameters, and even study different powertrain configurations. In particular, the paper describes the engine-in-the-loop study of a V-8, 61 engine coupled to a virtual 4×4 off road vehicle. This engine is considered as a high-performance option for this truck and the real prototype of the complete vehicle does not exist yet. The results shed light on critical transients in a conventional powertrain and their effect on NOx and soot emissions. Measurements demonstrate very large spikes of particulate concentration at the initiation of vehicle acceleration events. Characterization of transients and their effect on particulate emission provides a basis for devising engine-level or vehicle level strategies, and direct guidance for developing drive-by-wire systems and/or hybrid supervisory control.
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment