In the last years, emissions standards for internal combustion engines are becoming more and more restrictive, particularly for NOx and soot emissions from Diesel engines. In order to comply with these requirements, Original Equipment Manufacturers (OEM) have to face with innovative combustion concepts and/or sophisticate after-treatment devices. In both cases, the role of the Engine Management System (EMS) is increasingly essential, following the large number of actuators and sensors introduced and the need to meet customer expectations on performance and comfort. On the other hand, the large number of control variables to be tuned imposes a massive recourse to the experimental testing which is poorly sustainable in terms of time and money. In order to reduce the experimental effort and the time to market, the application of simulation models for EMS calibration has become fundamental. Predictive models, validated against a limited amount of experimental data, allow performing detailed analysis on the influence of engine control variables on pollutants, comfort and performance. In this paper, a simulation analysis on the impact of injection pattern and Exhaust Gas Recirculation (EGR) rate on fuel consumption, combustion noise, NO and soot emissions is presented for an automotive Common-Rail Diesel engine. Simulations are accomplished by means of a quasi-dimensional multi-zone model of in-cylinder processes. Furthermore a methodology for in-cylinder pressure processing is presented to estimate combustion noise contribution to radiated noise. Model validation is carried out by comparing simulated in-cylinder pressure traces and exhaust emissions with experimental data measured at the test bench in steady-state conditions. Effects of control variables on engine performance, noise and pollutants are analyzed by imposing significant deviation of EGR rate and injection pattern (i.e. rail pressure, start-of-injection, number of injections). The results evidence that quasi-dimensional in-cylinder models can be effective in supporting the engine control design toward the optimal tuning of EMS with significant saving of time and money.