Realfahrtests für die Antriebsentwicklung mithilfe des virtuellen Fahrversuchs

Donn, Christian; Zulehner, Wolfgang; Pfister, Felix

doi:10.1007/s35778-019-0030-6

Cited by 7 publications

(8 citation statements)

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“…In vehicle development, calibration tasks commonly use Model-in-the-Loop (MiL), Hardware-in-the-Loop (HiL) [10,11], and Engine-in-the-Loop (EiL) [12][13][14]. These X-in-the-Loop (XiL) test benches are increasingly used for testing real driving emissions and applications, as noted in numerous publication sources [15][16][17][18]. One advantage of these test benches is their high degree of flexibility.…”

Section: State-of-the-art-novel Methods For Vehicle Calibrationmentioning

confidence: 99%

“…Generic test cycles (e.g., ADAC BAB cycle or RTS95) are commonly used fleet-generically on chassis dynamometers and offer a high level of comparability and a low vehicle-specific effort. Real-world route retracing with operating point reproduction [27][28][29][30] can transfer realworld driving behaviors or environments to test benches or simulations, with the added ability to test different traffic scenarios [15]. Synthetically generated statistical driving profiles-primarily using Markov chains [31]-are utilized to represent regional driving behavior and are the focus of the research in [32][33][34][35][36][37].…”

Section: State-of-the-art-novel Methods For Vehicle Calibrationmentioning

confidence: 99%

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Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

Krysmon,

Pischinger,

Claßen

et al. 2024

Future Transportation

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Further reducing greenhouse gas and pollutant emissions from road vehicles is a major task for the automotive industry. Stricter regulations regarding emissions and fleet fuel consumption require the continuous development of new powertrains and methods. In particular, the combination of hybrid powertrains on the technical side and the focus on real driving emissions (RDE) on the legislative side pose significant challenges to the vehicle calibration process. Against this background, new test methods and environments are being investigated to counteract the high number of interactions between hybrid drive systems and quasi-infinite test conditions due to RDE. Complementary to new test environments, innovative methods for data analysis are needed that allow the exploitation of the complete potential of measurement data. The application of such a method in the field of emission calibration is presented in this paper. For this purpose, a clustering method (HDBSCAN) is applied to critical sequences from emission tests. Within this presentation, the clustering process is based on a single signal only. This paper shows how signals of various characteristics can be processed with dynamic time warping and generically structured with the clustering method used. Here, 959 single events are automatically categorized into 24 clusters. This provides a new basis for system evaluation, enabling the automatic identification, categorization, and prioritization of calibration weaknesses. Using twelve signals of different characteristics, the generic usability of the clustering method is demonstrated.

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Section: State-of-the-art-novel Methods For Vehicle Calibrationmentioning

confidence: 99%

Section: State-of-the-art-novel Methods For Vehicle Calibrationmentioning

confidence: 99%

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

Krysmon,

Pischinger,

Claßen

et al. 2024

Future Transportation

View full text Add to dashboard Cite

show abstract

“…State-of-the-art approaches extract route information from map and global position system (GPS) data to simulate the road gradients or, when used on an engine test bench, the curve radii of the selected route. 35,63–65 This procedure is not applicable in the newly introduced methodology of the RDE-cycle-generator for the exact reproduction of critical events for two reasons:…”

Section: Validation Of the Methodology By Implementation Of The Test mentioning

confidence: 99%

“…12 Manufacturers mainly investigate validation test matrices consisting of fleet-generic cycles and on-road tests with portable emission measurement systems (PEMSs) to assess whether the type approval tests can be passed. 35–37 The review of these methods in source 10 indicates that an adequate RDE validation cannot be guaranteed by this approach due to the insufficient consideration of individual characteristics of different vehicle types. 10 Current approaches either deal with the creation of geographically and regionally realistic driving scenarios or with synthetic profiles with significantly high driving dynamics aiming to cause maximized emissions.…”

Section: Current and Future Challenges To Comply With The Rde Requirementioning

confidence: 99%

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

Claßen

Pischinger

Krysmon

et al. 2020

International Journal of Engine Research

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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.

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“…The introduction of new test facilities is required to keep up with the exponential growth in tests to be carried out. The introduction of RDE has not only motivated the extensive use of virtual test capacities-such as Engine-in-the-Loop (EiL) testing on highly dynamic engine test benches-but also to the development of new validation processes [34][35][36]. Limiting the required number of tests to a reasonable number with sufficient resources, data-driven approaches are required to identify the status quo of a certain system and to make as much use as possible of the information contained in the data collected during the development process.…”

Section: Challenges Posed By Rdementioning

confidence: 99%

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

et al. 2021

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The combination of different propulsion and energy storage systems for hybrid vehicles is changing the focus in the field of powertrain calibration. Shorter time-to-market as well as stricter legal requirements regarding the validation of Real Driving Emissions (RDE) require the adaptation of current procedures and the implementation of new technologies in the powertrain development process. In order to achieve highest efficiencies and lowest pollutant emissions at the same time, the layout and calibration of the control strategies for the powertrain and the exhaust gas aftertreatment system must be precisely matched. An optimal operating strategy must take into account possible trade-offs in fuel consumption and emission levels, both under highly dynamic engine operation and under extended environmental operating conditions. To achieve this with a high degree of statistical certainty, the combination of advanced methods and the use of virtual test benches offers significant potential. An approach for such a combination is presented in this paper. Together with a Hardware-in-the-Loop (HiL) test bench, the novel methodology enables a targeted calibration process, specifically designed to address calibration challenges of hybridized powertrains. Virtual tests executed on a HiL test bench are used to efficiently generate data characterizing the behavior of the system under various conditions with a statistically based evaluation identifying white spots in measurement data, used for calibration and emission validation. In addition, critical sequences are identified in terms of emission intensity, fuel consumption or component conditions. Dedicated test scenarios are generated and applied on the HiL test bench, which take into account the state of the system and are adjusted depending on it. The example of one emission calibration use case is used to illustrate the benefits of using a HiL platform, which achieves approximately 20% reduction in calibration time by only showing differences of less than 2% for fuel consumption and emission levels compared to real vehicle tests.

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Realfahrtests für die Antriebsentwicklung mithilfe des virtuellen Fahrversuchs

Cited by 7 publications

References 0 publications

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

Applying Density-Based Clustering for the Analysis of Emission Events in Real Driving Emissions Calibration

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

Real Driving Emissions—Conception of a Data-Driven Calibration Methodology for Hybrid Powertrains Combining Statistical Analysis and Virtual Calibration Platforms

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