Comparative study of Vibe 2-Zone and Multiple Vibe 2-Zone combustion models on combustion, performance, and emissions of a diesel engine

• Vibe 2-Zone and multiple Vibe 2-Zone combustion models are investigated. • Their performance, combustion, and emissions are compared. • Multiple Vibe 2-Zone model produces higher cylinder pressure and temperature peaks than its counterpart at 15.47 and 2.07%, respectively. • Power and torque differences between two models are negligible, just 0.75 and 2.48%, respectively. • Their emissions differences are notable, with values up to 42.67, 7.52, and 11.34% for NOx, CO, and soot, respectively. This work evaluates the differences in combustion, performance, and emission characteristics between two combustion models of the Vibe 2-Zone and Multiple Vibe 2-Zone on a single cylinder diesel engine. The AVL Boost software was used to investigate the engine at its 85% load with differences in the PRs, ignition timings, and combustion durations. The simulation results based on the two combustion models will be analyzed and compared to show their similarities and differences. The findings indicate that there is an insignificant difference between the two models in terms of power, torque, and brake-specific fuel consumption. The highest differences between the two models are 0.75, 2.48, and 2.48% for power, torque, and brake specific fuel consumption, respectively. For peak cylinder temperature and pressure, the largest difference between the two models is 2.07% and 15.47%. The difference in emissions between the two models is quite significant, especially with NOx. The most considerable differences between the two models are 7.52%, 11.34%, and 42.67% for CO, soot, and NOx, respectively. The study highlights that the Vibe 2-Zone combustion model is preferable for engine performance simulations due to its advantages, including reduced input parameter requirements and time efficiency. However, the Multiple Vibe 2-Zone combustion model is recommended for greater accuracy, particularly in emission predictions.