Multiple injections and high EGR rates are now widely adopted for combustion and emissions control in passenger car diesel engines. In a wide range of operating conditions, fuel is provided through one to five separated injection events, and recirculated gas fractions between 0 to 30% are used. Within this context, fast and reliable multi-dimensional models are necessary to define suitable injection strategies for different operating points and reduce both the costs and time required for engine design and development. In this work, the authors have applied a modified version of the characteristic time-scale combustion model (CTC) to predict combustion and pollutant emissions in diesel engines using advanced injection strategies. The Shell auto-ignition model is used to predict auto-ignition, with a suitable set of coefficients that were tuned for diesel fuel. The standard CTC model was improved by introducing a new expression to compute the characteristic time-scale together with multiple time-scales that were considered to estimate the reaction rates of the chemical species. Soot emissions were predicted by the eight reaction step mechanism proposed by Fusco and the extended Zeldovich mechanism was used to estimate NOx concentration. The proposed combustion model has been implemented into the Lib-ICE code, which is a set of libraries and applications for IC engine modeling developed under the OpenFOAM® technology. The spray is described by using the conventional Eulerian-Lagrangian approach and the Huh-Gosman model is used to describe the primary atomization of the liquid jet. To validate the proposed approach in a wide range of operating conditions, a suitable methodology was developed to define a suitable case setup for any of them in terms of initial conditions and spray model constants. Experiments conducted in a common-rail, turbocharged diesel engine were used for experimental validation, and a detailed comparison will be provided between measured and computed data of in-cylinder pressure, heat release rate and pollutant emissions.