Mehdi Chelli

Renault Project : – Development of models for managing textual alerts across different clusters. – Implementation of new features and resolution of bugs for multiple clusters. – Automatic code generation and solution testing on a virtual control unit (Software-in-the-Loop – SIL). – Configuration and version management of the developed models.

Nissan Project: – Drafted specifications for the development of new tools. – Defined functional requirements for tools supporting engine tuning activities. – Supervised the developer in charge of tool development using Python and MATLAB. – Conducted functional testing and validation of tools prior to delivery. – Managed user communication during tool deployment and release. – Ensured configuration and version management of developed tools. – Provided technical support and user assistance for the tools.

– Quantification of the impact of the architecture of the cooling circuit on emissions according to Euro6D and Euro7 pollution control standards. – Analysis of test results. – Development of a simplified calculation model: cartographic model, based on the variation in the temperature of the coolant. – Computation and simulation of several cases depending on the configuration used. – Estimation of the penalty or the gain in pollutant production (NOx, Fine particles, CO, HC). – Communication of results and participation to the progress meetings.

– Development of a tool capable of detecting hot pollution inductors and quantifying the impact of each inductor. – Examination and analysis of the results of pollution control tests. – Processing of tests upstream: data structuring. – Association of emissions with driving inductors and engine control strategies (Start & Stop, high torque transient, re-coupling at idle, gear change, Take off). – Quantification of the impact of each inductor on hot emissions (coolant temperature above 30 ° C). – Development of an automatic test processing tool, this tool is capable of generating: – 1/ an Excel file containing the following information: quantification of the impact of each inductor in percentage and in mass (instantaneous and cumulative), information relating to the engines, cycles, standards, test chosen for analysis. – 2/ A second by second analysis, in the form of several graphs, associating the inductor of pollution and the moment of production of pollutants. – 3/ A graphical analysis in the form of Pareto containing the percentages of pollutant production for each inductor. – Development of a human / machine interface, in this interface the user is able to choose: – 1/ the test (s) to be analyzed. – 2/ the driving cycle (WLTC, NEDC, RDE ...) corresponding to the chosen test(s). – 3/ the engine (displacement: 1L, 1.2L, 1.3L, 1.6L, 1.8L) – 4 / The standard (Euro6D-temp, Euro6D-full, Euro7) – Statistical study on gasoline engines.

– Following the new regulatory constraint on particle emissions for gasoline engines, I joined the team in order to contribute to the modeling of a particle filter: – Examination and analysis of pollution control test results. – Development and digital calibration using the test results of a soot loading model (fine particles), it is a cartographic model based on: the relative torque, the engine speed, the temperature of the engine coolant, engine power. – Correlation of tests / simulations on different driving cycles and validation of calibrations. – Model assembly: loading, unloading, controller: The unloading model is used to show the reduction over time of the mass of soot in the particle filter, it was developed by an internal Renault team. The controller is used to define regeneration (unloading) thresholds, trigger active regeneration (there are two types of regeneration: passive (spontaneous) and active). – Estimation of the accident rate among customers by simulation: simulations are made on customer bases which are records of trip, vehicle speed, engine speed. The accident rate is the number of customers out of a sample of 1000 customers who should change the particulate filter after clogging. – Communication of simulation results for the passage of project milestones. – Assembly of a second supplier model and creation of interfaces (the inputs of the model to be able to simulate), for example: injection cut-off, end-of-start-up time counter, lambda probe active or not – Simulation and consolidation of calculations / results made with the first model.

– Integration of control laws of a hybrid vehicle in a co-simulation platform: – Creation of interfaces to adapt the control laws to the simulation platform – Integration of two control laws according to the hybridization architecture and the number of electric machines (one or two machines), the work consists in determining the torque demanded at each moment by the electric machine (s) according to the operating mode. – Simulation and estimation of the CO2 gain. – Recalibration of the simulation platform on the basis of the first tests on the vehicle.