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The challenges of ever increasing combustion engine complexity coupled with the introduction of new and ever more stringent emissions regulations place a unique strain on the time available during the base engine hardware development and calibration phase of the product development cycle. Considering state of the art gasoline engine architecture (dual variable valve timing, direct injection with turbocharger) it is common to have at least 12 degrees of freedom as system inputs. The understanding of interactions and inter-dependencies of these inputs is therefore key in optimising the performance of the engine. MAHLE Powertrain has developed a process using a global Design of Experiment (DoE) technique based on Gaussian processes that can be used to accurately model and optimise many aspects of an engine’s performance.

In 2012 MAHLE Powertrain developed a range-extended electric vehicle (REEV) demonstrator, based on a series hybrid configuration, and uses a battery to store electrical energy from the grid. Once the battery state of charge (SOC) is depleted a gasoline engine (range extender) is activated to provide the energy required to propel the vehicle. As part of the continuing development of this vehicle, MAHLE Powertrain has developed control software which can intelligently manage the use of the battery energy through the combined use of GPS and road topographical data. Advanced knowledge of the route prior to the start of a journey enables the software to calculate the SOC throughout the journey and pre-determine the optimum operating strategy for the range extender to enable best charging efficiency and minimize NVH. The software can also operate without a pre-determined route being selected.