Integrated numerical procedures for the design, analysis and optimization of Diesel engines

Both the design and analysis of a diesel engine requires the integration of accurate theoretical methods, resorting to 1D - 3D CFD modelling and vibro-acoustic engine analysis. In this chapter, the above numerical approaches will be deeply presented and integrated to perform a diesel engine design and/or analysis. As known in fact, the possibility to simulate the physical and chemical processes characterising the operation of internal combustion engines by using appropriate codes and high performance computers is continuously spreading. These simulations can predict, as an example, fuel consumption, toxic emissions and noise radiation. By varying the design and/or control parameters, different engine configurations or working conditions can be tested and their performances compared. Optimization techniques (Papalambros et al. 2000; Stephenson, 2008; Costa et al., 2009), properly matched with the various simulation procedures, are hence the most suitable tool to identify optimal solutions able to gain prescribed objectives on engine efficiency, power output, noise, gas emissions, etc.. The choice of the optimization goal, moreover, strictly depends on the application type and the definition of a compromise solution among the conflicting needs is in many cases required. Concerning the design of a combustion engine, a complicated and multi-objective task is to be afforded, since it generally requires the fulfilment of various objectives and constraints, as high efficiency and power output, low noise and gas emissions, low cost, high reliability, etc. A tool for multi-objective optimization, therefore, can be considered as fundamental at the engine design stage, in order to gain insight into the complicated relationships between the physical entities involved in the design and design-dependent parameters. Ultimately, optimization can greatly reduce the time-to-market of new engine prototypes. Optimization techniques can successfully be applied to analyze the operating conditions of existing engines, too. In this case, the optimization process can be focused on the selection of the control parameters in order to obtain an optimal engine behaviour. It is well known, in fact, that combustion development and emission production depend on a complex interaction among different parameters, namely injection modulation and phasing (Stotz et al. 2000), boost pressure, EGR fraction, swirl ratio, fuel properties, and so on. The optimal choice of a so large number of parameters depends on speed and load conditions, and it is related to the fulfilment of a number of contrasting objectives, like reduced NOx, Soot, HC, CO, fuel consumption and noise emissions