NOx Emission of a Correlation between the PEMS and SEMS over Different Test Modes and Real Driving Emission

The aim of this study is to verify the reliability of NOx emissions measured using Smart Emissions Measurement System (SEMS) equipment in comparison with the NOx emissions measured using certified Portable Emissions Measurement System (PEMS) equipment. The SEMS equipment is simple system, and it is less expensive than the PEMS equipment, as it comprises an On-Board Diagnostics (OBD) signal from the test vehicle and a NOx sensor. The SEMS equipment based on low-cost sensors has an advantage of building big data, but there are insufficient previous studies comparing of NOx emissions with certified the PEMS equipment. Therefore, this study is important in verifying the suitability of the SEMS equipment by comparing the NOx emissions measured by the various test modes and RDE using the two types of equipment. To analyze the correlation between the PEMS and SEMS equipment, the advanced diesel vehicle was equipped with the two types of equipment to simultaneously measure NOx emissions. After installing the equipment on the test vehicle, it was conducted under various test modes in the laboratory and the Real Driving Emission (RDE) test to verify the correlation of NOx emissions measured by the SEMS equipment. The correlation analysis for the NOx emissions measured by the PEMS and SEMS equipment under various test conditions and the RDE test indicated that the slope of the NOx emissions was approximately equal to 1, and the coefficient of determination was 0.9 or higher. Based on these test results, it was concluded that NOx emissions measured by the PEMS and SEMS equipment are highly similar.

Real Driving Emission Calibration—Review of Current Validation Methods against the Background of Future Emission Legislation

Reducing air pollution caused by emissions from road traffic, especially in urban areas, is an important goal of legislators and the automotive industry. The introduction of so-called “Real Driving Emission” (RDE) tests for the homologation of vehicles with internal combustion engines according to the EU6d legislation was a fundamental milestone for vehicle and powertrain development. Due to the introduction of non-reproducible on-road emission tests with “Portable Emission Measurement Systems” (PEMS) in addition to the standardized emission tests on chassis dynamometers, emission aftertreatment development and validation has become significantly more complex. For explicit proof of compliance with the emission and fuel consumption regulations, the legislators continue to require the “Worldwide Harmonized Light Duty Vehicle Test Cycle” (WLTC) on a chassis dynamometer. For calibration purposes, also various RDE profiles are conducted on the chassis dynamometer. However, the combination of precisely defined driving profiles on the chassis dynamometer and the dynamics-limiting boundary conditions in PEMS tests on the road still lead to discrepancies between the certified test results and the real vehicle behavior. The expected future emissions standards to replace EU6d will therefore force even more realistic RDE tests. This is to be achieved by significantly extending the permissible RDE test boundary conditions, such as giving more weight to the urban section of an RDE test. In addition, the introduction of limit values for previously unregulated pollutants such as nitrogen dioxide (NO2), nitrous oxide (N2O), ammonia (NH3) and formaldehyde (CH2O) is being considered. Furthermore, the particle number (for diameters of solid particles > 10 nm: PN10), the methane (CH4) emissions and emissions of non-methane organic gases (NMOG) shall be limited and must be tested. To simplify the test procedure in the long term, the abandonment of predefined chassis dyno emission tests to determine the pollutant emission behavior is under discussion. Against this background, current testing, validation, and development methods are reviewed in this paper. New challenges and necessary adaptations of current approaches are discussed and presented to illustrate the need to consider future regulatory requirements in today’s approaches. Conclusions are drawn and suggestions for a robust RDE validation procedure are formulated.

Machine Learning Applied to the NOx Prediction of Diesel Vehicle under Real Driving Cycle

Euro 6 standards impose stringent nitrogen oxide (NOx) emission limits on diesel cars. NOx emissions are significantly different between Euro 6 diesel cars and the previous standards in real-world driving. In this research, the NOx concentrations of Euro 6 diesel engines during real-world driving were studied considering various factors. Real driving emission (RDE) tests were conducted using vehicles equipped with portable emissions measurement systems. Urban, rural, and motorway test routes were utilized. Road environment, atmospheric, and after-treatment performance factors were collected in each case. An artificial neural network was used for evaluation using RDE test data and various statistical parameters. It was found that the proposed method predicted the pollutant emissions effectively. Lastly, the relative importance of each predictor was derived, and the NOx concentrations were analyzed. These approaches provide accurate emission information for an environmental effect evaluation that reflects more realistic road conditions.

Research on real-driving emissions of heavy tractor under different loads

The actual road diesel emissions of heavy-duty vehicle is very high, which has been a concern around the world. In 2018, Chinese government promulgated the "China VI" regulations containing real-driving emission test requirements and limits, requiring vehicle manufacturers to effectively control vehicle emissions to meet the requirements of China VI. This article takes a heavy-duty tractor equipped with a "China VI" engine as the research object, and performs actual road emission tests after loading 10%, 25%, 50%, 75%, and 100% respectively. The results show that NOx emissions are higher at low loads and PN emissions are higher at high loads, and CO emissions are not sensitive to load changes.

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

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.