Virtualization allows the simulation of automotive ECUs on a Windows PC executing in closed-loop with a vehicle simulation model. This approach enables to move certain development tasks from road or test rigs and HiL (Hardware in the loop) to PCs, where they can often be performed faster and cheaper. Renault has recently established such a virtualization process for powertrain control software based on Simulink models. If the number of runnables exceeds a threshold (about 1500) the execution of the virtual ECU is no longer straight forward and specific techniques are required. This paper describes the motivation behind a Simulink model based process, the virtualization process and applications of the resulting virtual ECUs. Domain: Critical Transportation Systems Topic: Processes, methods and tools, in particular: virtual engineering and simulation 1. Motivation Since 2010, Renault has established a framework to develop engine control software for Diesel and Gasoline engines [6]. The framework is heavily based on MATLAB/Simulink and the idea of model-based development, which facilitates the carry-over and carry-across of application software between software projects. In the Renault EMS architecture software is composed in to about 20 functions, such as Air System, Combustion etc. A function consists of modules. A module is the smallest testable software unit and contains runnables to be scheduled and executed by the Operating System (Os) of the ECU. The Renault EMS development process includes basically the following steps [5]. 1. Specification of about 200 generic configurable modules per ECU using MATLAB/Simulink. 2. Generation of C code (EMS application software) from all module specifications using MATLAB/Simulink Embedded Coder. 3. MiL (Model in the Loop) test and validation of the resulting executable specifications at module level in a simulated system environment, considering only essential interactions with other modules and system environment. This is essentially a back-to-back test to make sure that the Simulink model of a module and the corresponding production C code show equivalent and intended behaviour. To insure software quality, this step is repeatedly performed with steps 1 and 2, based on the simulation capabilities of MATLAB/Simulink. 4. Configuration of modules to fit to the specific needs of a software project, such as absence or presence of certain components. 5. Integration of generated configured C code and hand-coded platform software (basic software) on supplied target hardware, a real ECU that communicates with other controllers via CAN and other busses. 6. Validation and test of all modules on system level using the real ECU. In contrast to step 3, the interactions of all modules and interactions with the system environment are visible then and subject to testing. For example, the Os runs all scheduled runnables then, not just those of the modules considered to be 'essential' for a module under test. Critical assessment of the above process shows that there is a considerable delay between delivery of a set of specifications to the software project team (at the end of step 3) and system-level tests based on an ECU that runs entire software (step 6). Typical delays are weeks or months.