Investigation of auto-ignition combustion in a small two-stroke engine

Publication Type:
Issue Date:
Full metadata record
Files in This Item:
Filename Description Size
01Front.pdf7.05 MB
Adobe PDF
02Whole.pdf66.87 MB
Adobe PDF
NO FULL TEXT AVAILABLE. Access is restricted indefinitely. ----- This thesis investigates Auto-Ignition (AI) combustion in a small two-stroke engine. To the author’s knowledge, this is one of the few projects on AI or HCCI, in Australia, which has been published. AI is a novel mode of combustion for internal combustion (IC) engines. It has received wide interest due to the benefits of reduced exhaust emissions and excellent fuel consumption. The introduction of AI combustion to IC engines dates back to the late 1970s. Since then, the research into AI has been predominantly linked with IC engines used for automotive applications. However, AI applications in small engines, such as lawnmowers and generators, have received little attention in academic literature. Yet application of AI could result in the aforementioned benefits, even in smaller classes of engines. The investigation is mainly experimental based and conducted on a 160cc single cylinder two-stroke engine, which is originally applied for lawnmowers. Different strategies to achieve AI are investigated, and the original engine is modified to meet the conditions of AI. The charge temperature and air-to-fuel ratio are the two major requirements to be met. The key strategy to reach the required AI temperature is to use the thermal energy of internal exhaust gas recirculation (EGR) facilitated by an exhaust valve. The original carburettor is replaced by a fuel injection system in order to meet the requirement of the air-to-fuel ratio. The established test engine is the basis for the experimental investigation on AI, which is the main component of this thesis. The experimental investigation has two aims. The first is to determine the AI operation region and to gain an understanding of the characteristics of AI and the second is to study the effects of spark assisted AI (SA-AI) mode on AI operation. The operating region of AI for the test engine is found to be limited by insufficient in-cylinder temperatures at lower loads and by the amount of fresh charge that can be provided at higher loads. The characteristics of AI combustion such as the ignition timing, combustion duration, rate of heat release and stability are studied. The engine performance in AI operation is compared against that in Spark Ignition (SI) operation to demonstrate the improvement brought by AI. To reach the second aim, SA-AI mode is tested at various engine loads. The effect of SA-AI on cyclic variation and the effect of spark timing on AI are investigated. Results of AI with and without spark assistance are compared. The comparison shows a significant reduction of cycle-to-cycle variations under SA-AI mode. It also indicates that certain advancement of the spark timing is required to make the spark assistance effective and this required spark advancement depended on engine load and air fuel ratio. Also in this thesis, a computational fluid dynamics (CFD) model of the test engine is developed to study the in-cylinder distribution of the temperature and mixture of the fresh charge and the trapped burned gets prior to AI. The model simulates the process from the exhaust port opening to the point before ignition. The CFD model is validated against experimental results of cylinder pressure. Numerical simulations are performed using the validated model for different engine conditions. The temperature and distribution of mass concentration of the mixture in the cylinder are analysed to investigate the mixture formation for AI and the effect of internal EGR on AI. In summary, the investigations on AI provide important insights into the combustion characteristics unique to small IC engines. The results of investigation to the SA-AI technique show the great potential of this technique for controlling auto-ignition timing and improving engine operation stability.
Please use this identifier to cite or link to this item: