Statistically supported real driving emission calibration: Using cycle generation to provide vehicle-specific and statistically representative test scenarios for Euro 7

Abstract

<jats:p> The progression of emission legislation has intensified the efforts of the automotive industry to develop improved exhaust gas after-treatment systems. The requirement to fulfill Euro 6d-TEMP in real-world driving scenarios, the already significant calibration effort for Euro 6d and the Euro 7 emission standards in discussion have significantly increased the work load for calibration engineers and the requirements for testing resources. Many original equipment manufacturers are implementing taskforces in order not to have to discard the planned start of production for their products, and some are even already forced to reduce their product portfolio. This is due to the diverse testing matrix required to cover all possible real driving emissions test scenarios. One big challenge is the extension and possible variation of boundary conditions regarding ambient temperatures, traffic conditions, road gradients and other varying driving resistances. Moreover, the test duration can cause considerable differences in the measured emissions, even if the same route is driven repeatedly. Addressing these challenges makes the application of a dedicated, event-targeted emission calibration mandatory. Since only a few sequences of the time-consuming road tests are relevant for improving the emission calibration, the methodology presented in this article focuses on the exact reproduction of these emission events on an emission chassis dynamometer with the aim of implementing calibratable solutions for these events. This is done using a real driving emission-cycle-generator which creates real driving emission compliant severe test scenarios and which focuses on the statistical relevance related to the typical product specific operation. The underlying generation process accesses a large database with real driving emission measurement results focusing on vehicle- or vehicle-group-specific challenges, using statistical approaches. It will be demonstrated how this procedure reduces test time and how it helps to tackle the substantial real driving emission work-load, while providing a dependable base to achieve real driving emission legislation compliance. </jats:p>

Assessment and design of real world driving cycles targeted to the calibration of vehicles with electrified powertrain

“…Therefore, it is aimed to be applicable to all the different hybrid and plug-in hybrid vehicles. Thus, the proposed velocity profiles, as derived from the analysis, can be used in different stages of the powertrain design, like the component size selection, or the system calibration, 5 and serve as the starting point for simulationbased development 6,7 or assessment of electrified vehicles.…”

Prediction of gaseous pollutant emissions from a spark-ignition direct-injection engine with gas-exchange simulation

“…However, the current and future emission regulations, under consideration of the RDE, require a higher degree of virtual development and optimization of engine raw emissions. 6 The possibility to predict engine emissions in a concept phase is of crucial importance for a fast and cost-effective development of new lowemission vehicle concepts (hybrid, range-extender, etc.). This possibility allows the evaluation of different vehicle concepts and can support the decision on hardware and system components already in the concept phase.…”

Development of a Novel Gasoline Particulate Filter Loading Method Using a Burner Bench

“…To reduce the effort needed for engine control unit (ECU) calibration and validation, novel methodologies need to be adapted. In this context, novel strategies for ensuring RDE compliance have already been developed to cope with the extensive test matrix required to effectively cover all possible RDE scenarios [18][19][20][21]. Furthermore, as part of 'Road-to-Rig-to-Desktop' initiatives, several approaches towards virtual powertrain development, including so-called X-in-the-loop approaches, have already extensively been discussed in the literature [22][23][24][25][26][27][28][29].…”