Engine Simulations

Hybrid Electric Vehicle Engines

TECAT Engineering has developed an algorithm to predict the performance and emissions for families of engines used within a hybrid electric vehicle simulator. This algorithm has been incorporated into the ADVISOR and PSAT Hybrid Electric Vehicle models. ADVISOR is the ADvanced VehIcle SimulatOR developed at the National Renewable Energy Laboratory. PSAT, the Powertrain System Analysis Toolkit, was developed by Argonne National Laboratory and is sponsored by the US Department of Energy. Both tools have been developed to assist the automotive engineering community to quickly simulate the performance of a large number of vehicle design options.

This TECAT Engineering algorithm is based on a scalar model of existing engines. Taking user defined bore and stroke, the algorithm predicts the brake specific quantities of NOx, CO and fuel consumption. An oil film adsorption/desorption model and a crevice flow model have been added to the algorithm to predict exhaust hydrocarbons as well. The resulting emissions and performance maps at various engine displacements are then used within one of the HEV simulators mentioned above, to determine optimal sizing between the internal combustion engine and the electric drive system, subject to known driving schedules and charging strategies.
The scaling algorithm uses steady state data engine data and scaling factors generated from simulated WinKiva results for various combustion chamber shapes. The engine data and scaling factors are then combined to predict performance and emissions data for any engine size. When steady state engine data is not available, the algorithm can extract the data from transient engine schedules. This technique has been numerically validated by comparing actual steady state simulated maps with steady state maps created from transient schedule simulations. At each bore and stroke, a torque vs. speed sweep is performed to evaluate performance and emissions over the entire engine map. The scaling algorithm can then interpolate within the resulting data for any bore, stroke, torque and speed input. The algorithm may easily be expanded to include the effects of operating conditions such as the injection/spark timing.  
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