Modelling and calibration of high-pressure direct injection compressed natural gas engine - Mohd Fadzil, Abdul Rahim (2021)
This study deals with the modelling and optimisation of a High-Pressure Direct Injection Compressed Natural Gas (HPDI-CNG) system in a passenger vehicle. The effectiveness of the HPDI-CNG system needs to be assessed due to its novel and distinctive design. A comprehensive analytical model is required to simulate dynamic vehicle testing. The converted gas direct injector needs to be recalibrated. A simpler calibration method is necessary to reduce the experimentation burden. An optimal Artificial Neural Network (ANN) model is required to facilitate model-based calibration (MBC) procedure. A proper setting for the MBC procedure using the Genetic Algorithm (GA) needs to be identified. The objectives of the study are 1) to analyse the effect of HPDI-CNG system configuration and influential parameters, 2) to evaluate the injector mass flow rate and its suitability to fulfil engine requirement, 3) to assess the HPDI-CNG vehicle performance as a whole, and 4) to calibrate the electronic control unit (ECU) base maps by using MBC procedure. The ultimate goal of the study is a complete evaluation of the HPDI-CNG system. The methodology consisted of analytical vehicle modelling for transient vehicle operation and independent injector analytical modelling and testing. It follows by the HPDI-CNG vehicle testing using chassis dynamometer with the main assessed parameters is the engine brake torque and power, brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC). The MBC procedure was carried out by using the MBC Toolbox of Matlab. The calibration framework consists of the development of the data-driven model by using ANN and ECU parameters optimisation by using GA. Based on stated methodologies, the following findings were recorded; the analytical model of the HPDI-CNG vehicle predicted a maximum of 123.11 Nm of brake torque at 60 bar of injection pressure. The maximum mass flow rate obtained by the injector test is about 1.24 g/s at 60 bar injection pressure. Measured peak brake torque and power is about 69.6 Nm and 19.1 kW, respectively. The MBC procedure on the ECU maps has proven to be able to increase the overall performance of the HPDI-CNG engine. The best improvement recorded from the optimisation verification for the brake torque, brake power, engine rotational speed, BSFC, and BTE is 5.76%, 23.46%, 11.93%, 12.10% and 16.04%, respectively, based on mean percentage error. In conclusion, the analytical vehicle model able to predict the ideal engine performance. The most influential parameters are injection pressure, injection duration, and ignition timing. Ideally, the injector is found to be able to fulfil engine requirements until 6000 rpm for stoichiometric combustion. The configuration of HPDI-CNG is less efficient based on the current geometrical configuration. It reduced air intake or the engine's volumetric efficiency. It also affected the engine response, especially the maximum engine rotational speed, due to the delay in the fuel delivery. The optimization results suggested the use of the speed-sweep test method is sufficient for calibration purposes with reduced test-point. The impact of the study on the body of knowledge is a generation of a comprehensive evaluation of the HPDI-CNG configuration, which is based on analytical and data-driven model simulation and experimental testing. The model-based calibration procedure performed in the study provides a detailed methodology for performance improvement by calibrating the ECU maps.