An Optimal Method for Prediction of Engine Operating Points for an Effective Correlation in Fuel Economy Benchmarking

It is imperative that all automobile manufacturers conduct vehicle level benchmarking at the initial stage of any new project. From the benchmark information, the manufacturers can set relevant targets for their own vehicles under development. In this regard, an accurate prediction of the engine operating points can improve the correlation of the measured fuel economy of the benchmark vehicle. The present work describes a novel method that can be used for the accurate prediction of the engine operating points of any benchmark vehicle. Since the idea of instrumenting the crankshaft/driveshaft with torque transducers is a costlier and time-consuming process, the proposed method can be effective in reducing the benchmarking. Hence, the objective of this work is to develop a mathematical model to calculate the real-time engine operating points (engine speed and torque) using parameters like vehicle speed, accelerator pedal map, driveline inertia, vehicle coastdown force and gradient. This novel method is automated using a 1-dimensional mathematical tool Matlab. Moreover, the results of the predicted engine operating points are validated in one of the test vehicles of Mahindra and Mahindra by comparing with the torque values measured from the engine control unit (ECU). Furthermore, transient dynamometer measurement using AVL ISAC software was conducted and found that the measured operating points of the engine are having an excellent correlation of 98% with the predicted operating points. Thus, the proposed method could be considered as an optimal approach for the calculation of the real-time engine operating points of any of the benchmark vehicles.