Tese: Numerical Study of Spark-Assisted Compression Ignition Engines (SACI)
Aluno(a) : Caio Filippo Ramalho LeiteOrientador(a): Sergio Braga e Florian Pradelle
Área de Concentração: Termociências
Data: 04/10/2021
Link para tese/dissertação: https://doi.org/10.17771/PUCRio.acad.56816
Resumo: In the last few years, the automotive industry has reinvented itself to meet the demands of the international market, which has been increasingly competitive in a context with environmental laws each year more severe. One alternative to lower harmful greenhouse gases emissions over the life of the vehicle is electric cars. However, the production and disposal of electric batteries is still a major problem to be solved. Therefore, companies are also searching for other potentialities to increase the internal combustion engine's efficiency and develop green technology, such as Homogeneous Charge Compression Ignition (HCCI) or Spark-Assisted Compression Ignition (SACI). A MATLAB routine was created to predict the performance of SACI multi-mode combustion of natural gas using a two-zone thermodynamic model. This work performs sensitivity analysis for five performance parameters: thermal efficiency (η_th), indicated mean effective pressure (IMEP), NOx emissions, mean in-cylinder temperature (T ̅_avg), and auto-ignition timing (AIT), with several variables such as engine speed, fuel-air equivalence ratio, spark timing, compression ratio, and intake pressure, using the design of experiments tools to assess the factors’ impact. The Central Composite Design indicates that the engine speed and the fuel-air equivalence ratio were the most important SACI factors since they influence all engine performance parameters. On the other hand, the intake pressure was significant in three performance parameters (η_th, IMEP and T ̅_avg), as was the spark timing (NOx, T ̅_avg and AIT). The compression ratio, however, was relevant in only one of them (AIT). Furthermore, a Univariate Analysis was done to compare Spark-Ignition (SI) and SACI combustion techniques. The results show that at the same regime as traditional SI engines, SACI engines tend to be around 9% more efficient, NOx emissions drop notably, more than 99%, IMEP presents an increase of 45.4%, and T ̅_avg decreases 24.8%.