New methods are required for efficiently achieving the development goals of future powertrains. APL describes the use of new tools based on genetic algorithms for the targeted parameter optimisation and analysis of large amounts of data using syntactic and statistical pattern recognition. New processor and memory technologies increase the analysis performance of complex calculations and simulations and efficiently support the calibration process. ECU calibrations can already be prepared in offline applications as part of SiL (Software-in the-Loop) studies and thus reduce the effort on the test bench or in the vehicle.
REQUIREMENTS FOR THE CALIBRATION OF POWERTRAINS
In addition to the WLTP test cycle (Worldwide harmonized Light vehicles Test Procedure), with the introduction of the Euro 6d-temp legislation, the real driving emissions according to the RDE (Real Driving Emissions) test procedure must also be met for the homologation of new vehicle types. As reported in [1], APL has developed a general development approach to meet the challenges of WLTP and RDE in powertrain development. In addition to the consideration of extended engine map ranges with regard to speed and load, the emission calibration of powertrains with a conventional internal combustion engine must also take into account the influence of transient phases and dynamic effects. As part of the vehicle and driveability calibration, the torque structure, the engine-transmission interaction and the resulting load point shifts must then also be used to optimise emissions.
In an RDE-optimised development process, the goal is to provide a first proof of emissions for various variants and hybrid derivatives of a powertrain family already at the completion of the predevelopment phase, 1. The incorporation of the engine and powertrain test benches into a real-time vehicle simulation environment to model the vehicle, driver influence and environmental boundary conditions ensures a time-optimised measurement and calibration process with very good reproducibility and allows assessment of powertrain variability, such as vehicle inertia and dynamic gradients. Combined with high-resolution exhaust gas measurement technology, as well as mass and particle spectrometers, the engine behaviour and functional relationships can be described during dynamic driving cycles. This can be supplemented with optical investigations in the combustion chamber to analyse phenomena within individual work cycles [2, 3].
This story is from the September 2018 edition of Auto Tech Review.
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This story is from the September 2018 edition of Auto Tech Review.
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