Crank-rocker (CR) engine is a new kind of combustion engine that has a curved-cylinder combustion chamber. To enhance CR engine development and performance, high accuracy modeling which accurately predicts combustion characteristics is required. Due to the difference in cylinder configurations, the first empirical-model used to predict the combustion characteristics of a conventional engine may not be applicable. Currently, only a single correlation model has been proposed for CR engine. The main aims of this study are to improve the existing developed CR engine model and to investigate the impact of various heat transfer correlations in predicting combustion characteristics using single-zone combustion modeling. The model has been improved by including a sub-model of the specific heat ratio which varies with temperatures. Four cases of models incorporating various heat transfer correlations namely Woschni, Sitkei, Hohenberg, and Annand have been simulated. Then, the results were analyzed and compared with experimental data. Further simulations have been carried out to predict maximum pressures, temperatures, heat transfer coefficients, etc. under various loads. Annand's model was found to yield the best prediction for the combustion characteristics and it is considered the best choice concerning the accuracy and other criteria such as time and ease of usage.

Crank-rocker Gasoline Engine Test Rig and Experimental Set-up

The MATLAB script model code begins by specifying input variables for a compression-ignition (CR) engine, such as stroke and compression ratio. It calculates various engine parameters like cylinder head area, engine displacement, and piston speed. Blair's equation is used to determine friction losses. The script computes piston displacement, transmission angle, crank angle, and swing angle to derive the overall cylinder volume. Air-fuel ratio is determined through stoichiometric reactions, lambda reading, and balanced equations. Combustion characteristics, in-cylinder fuel mass, and Weibe equation are also calculated. In-cylinder residual gas fraction is determined using polytropic relationships. MATLAB script codes are used to analyze engine variables such as rate of heat release and pressure trends. The final model, named the 'Modified CR Model,' excludes heat transfer correlation models. Four additional models are developed for heat transfer evaluations using various correlations. The study involves simulations under different operating conditions, considering the impact of engine load on heat flux and heat transfer coefficient. Experimental data for certain operation loads are unavailable, so simulations are conducted for further investigation

Indicated Cylinder Pressure Vs. Crank Angle Comparison for Various Correlations (left) and Maximum Pressure Variation According to Correlation (right) for 100% Load

The study aims to enhance the accuracy of the combustion model by incorporating different heat transfer correlations. This is crucial for better predicting the behavior of the engine under various operating conditions.The study compares four different heat transfer correlations (Hohenberg, Woschni, Sitkei, and Annand) to determine their impact on the model outputs. The identification of the Annand correlation as the best for CR engine combustion modeling implies a significant impact on the accuracy of predictions.The analysis of maximum pressures and temperatures under different conditions provides valuable insights into the engine's performance. The findings, such as Hohenberg and Annand methods predicting the highest maximum pressure and temperature, contribute to understanding combustion characteristics.

The Heat Transfer Coefficients Comparison

Research and Development Opportunities: Companies involved in engine design and development may find opportunities to further research and develop models based on the correlations highlighted in the study.

Collaboration Potential: The study could open avenues for collaboration between researchers, engine manufacturers, and software developers aiming to improve combustion models for spark ignition crank-rocker engines.

Market Dynamics: The market potential is influenced by the demand for more accurate combustion models in engine development, emissions reduction efforts, and advancements in computational methods for simulations.