Real Driving Emissions Test Research Articles

NOx reduction scenarios under real-world driving conditions for light-duty diesel vehicles

This study analyze analyzes the impact of stringent emissions regulations on future NOx reductions. Using scenario analysis, NOx emissions of diesel light-duty vehicles from 2019 to 2040 are estimated using emission factors from real driving emissions data. The baseline scenario assumes current regulations will be maintained, while other scenarios assess the impact of implementing specific Euro standards as final regulations. If Euro 5 regulations are implemented by 2040, cumulative emissions will increase by 229.1 % compared to the baseline scenario. Implementing Euro 6 a/b/c regulations will increase by 156.2 %, while Euro 6 d-temp and Euro 6 d regulations will increase by 8.4 % and 0.7 %, respectively. These findings highlight the significant contribution of real driving emission test introduced with Euro 6 d-temp to NOx reduction. Furthermore, they indicate that Euro 6 d regulation has already achieved emission levels similar to those of the upcoming Euro 7 regulation.

Correlation relationships of processes in the combustion engine in the RDE test

The article presents considerations on the processes taking place in the combustion engine in the in real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel consumption, and the vehicle speed, which determines the engine operating conditions. The RDE test were carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle speed, control, rotational speed, relative torque and relative engine power, emission pollutant intensity of: carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle movement in cities, the second – outside cities, and the third – on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel consumption were determined in relation to the average vehicle speed, and based on these results, the exhaust emissions and fuel consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the measured variables combinations were determined.

Development of Driving Robot and Driver Model Applied Regenerative Brake Control of Electrified Vehicles

Real driving emissions (RDE) test procedures for type approval were initiated in Japan in 2022. In Japan, the test vehicle is driven on a test road (test course) by tracing the speed pattern prepared for each RDE test. The vehicle needs to trace the patterns in the same manner as in the conventional chassis dynamometer test. The use of a driving robot is effective for reproducibility in precisely tracing the target vehicle speed during these tests. In this study, we developed a driving robot for electrified vehicles (HEV, plug-in HEV, BEV, and FCV), which have regenerative brake-control systems. We applied a new logic to our robot that was developed in-house for conventional engine vehicles. We focused on braking deceleration of the regenerative brake control to change the operation timing from the accelerator pedal to the brake pedal. We verified the improvement of speed traceability of the driving robot installed with the proposed logic on the chassis dynamometer and test road.

Impact of Mid-to-Low-Ash, Low-Viscosity Lubricants on Aftertreatment Systems after 210,000-Kilometer Real-World Road Endurance Trials

Engine lubricants globally face the challenge of meeting the demands of new engine technologies while enhancing energy efficiency and reducing emissions. Lubricants must enhance their performance and sustainability, improve reliability in complex and harsh environments, and minimize environmental impact and health risks. This study explores the influence of two different formulations of low viscosity lubricants, tested through actual road endurance trials, on a hybrid vehicle’s aftertreatment system performance and overall emission levels. The study includes 120,000 km of endurance testing in four different challenging environments in China, as well as 90,000 km of endurance testing in a typical urban and highway driving cycle in a large city. Results indicate that emissions from the test vehicles during the 120,000 km and 210,000 km durable Worldwide harmonized Light vehicle Test Cycles (WLTCs) meet China’s Stage 6 light-duty vehicle emission standards, with the 210,000 km Real Driving Emission test (RDE) results also conforming to these standards. Relative to fresh TWC, the light-off temperature increased by a mere 60 °C, and the oxygen storage capacity declined by around 19% following endurance testing. Additionally, the GPF exhibited satisfactory performance after 210,000 km of endurance testing, showing lower backpressure values compared to the fresh-coated samples, with no notable ash buildup observed in the substrate. Drawing on the outcomes of actual road endurance testing, this study illustrates that employing low-to-mid-ash-content, low-viscosity lubricants is both compatible and reliable for aftertreatment systems in present or advanced hybrid technologies. Premium lubricants facilitate vehicles in sustaining compliant and stable emission performance, even amid harsh environments and complex operating conditions. Furthermore, the tested lubricants effectively inhibit excessive aging of the aftertreatment system over prolonged mileage. Moreover, this study discusses the feasibility of rapid aging evaluation methods for aftertreatment systems based on engine test benches, juxtaposed with actual road endurance testing. These findings and conclusions offer crucial references and guidance for enhancing lubricant performance and sustainability. Subsequent studies can delve deeper into the correlation between lubricant performance and environmental impact, alongside optimization strategies for lubricants across various vehicle models and usage scenarios.

Impact of diesel/renewable fuels blend on gaseous and particle emissions of a light-duty vehicle under real driving emissions

In this study, the environmental impact of Bio-butanol (BB) and Hydrotreated Vegetable Oil (HVO) use, each blended with diesel fuel, was investigated. To this aim, pollutant emissions were measured at the exhaust of an Euro 5 commercial light-duty vehicle, fueled with diesel, BB/diesel blend (10 %v BB) and HVO/diesel blend (15 %v HVO). The experimental activity was realized by performing Real Driving Emission (RDE) tests in Napoli (Italy), which allowed to measure total hydrocarbons (THC), carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOX), and particle emissions during the real use of vehicle by using a portable emission measurement systems (PEMS). The results show that the differences between fuels are small and not statistically significant for all emission parameters. CO and THC emissions increase with the renewable fuel blends, mainly with the BB blend in the urban environment due to the increasing of cold start contribution. NOX emissions increased with BB (by approximately 4 %) and decreased with the HVO (by approximately 13 %). With both renewable fuel blends, particle emissions at engine output were reduced by 25 %–41 % and fuel consumption by 6 %–10 % compared with diesel.

Comparison of the Real-Driving Emissions (RDE) of a Gasoline Direct Injection (GDI) Vehicle at Different Routes in Europe

On-road real-driving emissions (RDE) tests with portable emissions measurement systems (PEMS) are part of the vehicle emissions regulations in the European Union (EU). For a given vehicle, the final emission results depend on the influence of the ambient conditions and the trip characteristics (including the driver’s behaviour) on the vehicle performance and the instrument measurement uncertainty. However, there are not many studies that have examined the emissions variability of a single vehicle following different routes. In this study, a 1.2 L gasoline direct injection (GDI) Euro 5b passenger car without a particulate filter and a PEMS was circulated in seven European laboratories. At their premises, the laboratories performed two to five repetitions of on-road trips compliant with the EU RDE regulation. The ambient temperature ranged between 7 °C and 23 °C. The average emission levels of the vehicle were 135 g/km for CO2, 77 mg/km for CO, 55 mg/km for NOx, and 9.2 × 1011 #/km for particle number. The coefficient of variance in the emissions following the same route was 2.9% for CO2, 23.8% for CO, 23.0% for NOx, and 5.8% for particle number. The coefficient of variance in the emissions following different routes in Europe was 6.9% for CO2, 9.1% for CO, 0.0% for NOx, and 9.1% for particle number. The previous values include the specific vehicle emissions variability under the narrow test conditions of this study, but only partly the PEMS measurement uncertainty because the same instrument was used in all the trips. The results of this study can be used by laboratories conducting RDE tests to assess their uncertainty budget when testing or comparing vehicles of similar technology.

Type B uncertainty evaluation for real driving emission test based on second-by-second data

Type B uncertainty evaluation for real driving emission test based on second-by-second data

Study on Control Strategies on NOX Emissions to Meet Real Driving Emissions.

The aim of this study was to fulfill the NOx emissions standards for a light-duty diesel vehicle under real driving emissions (RDE) testing conditions by implementing various control strategies. In this study, RDE tests were performed by adjusting the air mass quantity and postinjection quantity in order to analyze engine-out and tail-pipe nitrogen oxides (NOx) emissions for different phases of RDE. The results showed that reducing in air mass quantity enabled the engine to operate in higher exhaust gas recirculation (EGR) rate regions, resulting in a 32.5% reduction in engine-out NOx emissions and an 80.4% decrease in tail-pipe NOx emissions. Increasing the postinjection quantity primarily enhanced the NOx conversion efficiency for the urban phase by 7.5%, leading to a 22.6% reduction in tail-pipe NOx emissions. By employing both strategies, vehicles can comfortably meet the CN6b emission regulations by a substantial margin.

Effect of ambient high-temperature on real driving emission tests of a light-duty gasoline vehicle

In real driving emission (RDE) test procedures, the extended high-temperature conditions of 30–35 °C are set to correct for the effect of ambient high-temperature on RDE tests. However, direct test data supporting or explaining the rationality of this provision remains lacking. To understand the impact of high-temperature environmental conditions on the RDE tests, ten RDE tests of a light-duty gasoline vehicle were conducted in an ambient temperature range of approximately 10–40 °C with the same driver and driving route. From the sample data of the ten RDE tests, the RDE tests were more affected by the non-temperature test conditions of trip dynamic, route topography, etc., than by the ambient temperature test conditions. The CO2, CO, NOx, and PN emissions were not sensitive to the variations in ambient temperature except for very few cases in urban CO2 and CO emissions. The ambient high-temperature conditions did not necessarily lead to severe pollutant emissions in the ten RDE tests. Extending the upper limit of the moderate temperature conditions upwards to a higher ambient temperature in the RDE test procedures should be considered.

Prediction of instantaneous particle number for light-duty gasoline vehicles under real driving conditions based on ensemble learning

With increasingly stringent emission regulations for particle number (PN) from real driving emissions (RDE), accurate prediction and evaluation of instantaneous PN emissions from RDE test is becoming increasingly important. However, there is still a lack of reliable PN emission prediction models for RDE test due to the complex nonlinear relationship between various affecting factors and PN emissions. Therefore, this study conducted RDE tests on a light-duty gasoline vehicle to acquire 10,646 sets of data, and four ensemble learning algorithms (randomforest, xgboost, catboost, and lightGBM) were introduced to construct prediction models of instantaneous PN emissions. Based on these models, the importance of 9 features affecting PN emissions was discussed using the Spearman correlation analysis and Shapley Additive Explanation (SHAP) algorithm. Among them, carbon dioxide share of exhaust (CO2,ratio), acceleration, vehicle specific power (VSP) and engine speed were identified as the critical input features. The catboost model has the optimal performance in prediction accuracy among the four models, with an average R2 and RMSE of 0.832 and 0.00253 respectively for the 10-fold cross-validated. Further analysis of the PN prediction results on different types of roads showed that the catboost model has high accuracy for instantaneous PN emissions on urban, rural and motorway trips. Moreover, the SHAP summary plot was employed to reveal the prediction mechanism of catboost algorithm through quantifying the feature contribution. The prediction model for instantaneous PN emissions provided a methodological reference for constructing vehicular emission models for RDE test.

Exhaust Emissions from Euro 6 Vehicles in WLTC and RDE—Part 2: Verification by Experimental Measurement

The subject of assessing exhaust emissions in real driving conditions has been relevant for a long time. Its introduction into approval tests focused attention on the comparative possibilities of tests performed on a chassis dynamometer and in road conditions. The article is a continuation of research on the possibilities of estimating emissions in the Real Driving Emission test based on emission data from Worldwide harmonized Light Vehicles Test Cycles. The first part discussed the possibility of comparing dynamic parameters in these tests, and the second part discussed the possibility of estimating road exhaust emissions. The work was done in two stages: the first stage involved the use of distance-specific emissions in individual parts of the WLTC test, and the second stage involved the use of exhaust emission rates as datasets divided into intervals defined by vehicle speed and acceleration. Comparative tests were performed for conventional vehicles (gasoline, diesel) and hybrid vehicles. A chassis dynamometer was used to carry out WLTC tests and PEMS equipment was used for the RDE tests. The exhaust gas components that had to be measured in road tests, namely: carbon monoxide, carbon dioxide, nitrogen oxides, and the number of particulate matter, were analyzed. Based on the data collected, parameters such as road emissions and the exhaust emissions rate were determined for each phase of the dynamometer test as well as the road test. Because of this, it was possible to compare the distance-specific exhaust emissions of each vehicle in the two emission tests. The comparison resulted in establishing that it is possible to estimate distance-specific exhaust emissions of conventional and hybrid vehicles in road test conditions, using only the results obtained in the approval test (for selected test phases). The research concluded that it is possible to estimate selected RDE test parameters based on the results obtained in the WLTC test for the tested vehicles.

The impact of the variation in driving conditions on the NOx emissions characteristics in PEMS test for heavy-duty vehicle

The real driving emission test using a portable emission measurement system is the advanced solution to assess NOx emissions from heavy-duty vehicles in recent years. To reflect the NOx emissions of heavy-duty vehicles more realistically, the restrictions on driving conditions will likely be relaxed in the next emission standard for heavy-duty vehicles. In this study, several tests with different payloads were conducted on a China VI heavy-duty vehicle under two different driving conditions. The test results show that some NOx emissions “spikes” may occur in any driving type during the tests of heavy-duty vehicles, and they are mainly related to the NOx conversion efficiency of the SCR system. In general, there is no obvious relevance between the NOx emission rate and the driving type, but the increase of the vehicle speed is beneficial to maintain the temperature of the SCR system in the high-efficiency zone, thus reducing the NOx emission rate. The variation of driving conditions will cause a change in the valid windows of the test, which will lead to a change in the evaluation results of NOx emission compliance. Adding motorway driving to the test route significantly increases the power threshold of the valid windows and reduces specific NOx emissions of the valid windows, with a minimum reduction of more than 30% and a maximum reduction of nearly 50% for “SENOx-90” in this study. The variation in driving conditions can severely affect the true NOx emissions assessment, especially for low-payload tests. In this study, the difference in NOx emissions assessed due to variation in driving conditions reached 1/3 of the total NOx emissions and the difference will gradually decrease as the vehicle load increases.

Traffic Flow Pattern Based Approach to Predict Real Driving Emission Test Routes

Due to the poor representation of NEDC emission test, the European Commission put into the force a new procedure, which contains both a laboratory test and a real word driving test. In this new test procedure, even though WLTC replaces NEDC, it is required to test the vehicle under real traffic conditions, which contains urban, rural and highway segments. Due to the new emission regulation, considerable number of academic work focus on the creation of RDE (Real Driving Emission) routes and RDE tests. In this study, it is introduced a new methodology for creating potential RDE routes. The routes, created in MATLAB code by using Istanbul road data containing a half an hour average trip records were used to predict a probable RDE test road. This model creates a number of RDE routes starting from defined coordinates and then analyses all alternative routes with respect to traffic flow rate and RDE boundary conditions identified by the European Commission. The routes obtained using the methodology developed are tested in real life conditions and evaluated according to actual existing traffic conditions. The agreement between the results of the method and the results of the actual driving test is limited in urban road section. However, for rural and highway road sections, there is a significant agreement between the predictions and actual test results.

Analysis of exhaust emission processes during the Real Driving Emissions test

The article deals with the study of exhaust emissions from a combustion engine in the Real Driving Emission (RDE) test. These tests are a simulation of real conditions of use of motor vehicles. Nowadays, RDE tests are mandatory for Light Duty Vehicle (LDV) and Heavy Duty Vehicle (HDV) vehicles and in the future, restrictive standard. Euro 7, which combines stricter limits with a comprehensive RDE test cycle, is becoming a challenge for current vehicle engineering. The paper presents the results of pollutant emission tests from a passenger car (PC). In the tests of LDV in the RDE test, the results of which are analyzed in the article, the Portable Emissions Measurement System (PEMS) mobile exhaust emission testing system was used. The processes describing the operating states of the vehicle and the combustion engine, as well as the processes of exhaust emission intensity and the intensity of the number of particulate (PN), were examined. The correlation between the considered processes was investigated. The emission of carbon monoxide, hydrocarbons, nitrogen oxides, particulate and carbon dioxide as well as the road PN were examined. The zero-dimensional statistical characteristics of the examined processes were also determined. The probability density and power spectral density of the processes were established. A great diversity was found in the properties of the process distributions, as well as in the dynamic properties of the processes. In the summary of the analysis of the results of the car speed process, the operating states of the combustion engine and the processes of exhaust emission intensity and the process of the intensity of PN in the RDE test, conclusions were formulated regarding, among others, course of the intensity of these compounds, correlation of the processes of pollution emission intensity and the intensity of the PN with the process of car speed, distribution of processes.

NOx emission deterioration in modern heavy-duty diesel vehicles based on long-term real driving measurements

NOx emissions from diesel vehicles generally deteriorate with increased durability mileage owing to the wear and deterioration of engines and after-treatment systems. Three China-VI heavy-duty diesel vehicles (HDDVs) were selected for four-phase long-term real driving emission (RDE) tests using the portable emission measurement system (PEMS). After 200,000 km of on-road driving, the maximum NOx emission factor of the test vehicles (387.06 mg/kWh) was found to be significantly lower than the NOx limit of 690 mg/kWh. Under all driving conditions, the NOx conversion efficiency of selected catalytic reduction (SCR) decreased almost linearly as the durability mileage increased. Importantly, the deterioration rate of the NOx conversion efficiency in low-temperature intervals was discernibly higher than that in high-temperature intervals. The NOx conversion efficiency at 200 °C dropped by 16.67–19.82% with higher durability mileage; however, the highest values at 275–400 °C only decreased by 4.11%. Interestingly, the SCR catalyst at 250 °C showed strong NOx conversion efficiency and durability (maximum decline of 2.11%). Overall, the poor de-NOx performance of SCR catalysts at low temperatures significantly challenges the long-term effective control of NOx emissions from HDDVs. Thus, improving the NOx conversion efficiency and durability at low-temperature intervals is the top priority for SCR catalyst optimization; NOx emissions from HDDVs at low velocities and loads should also be monitored by environmental authorities. The linear fitting coefficient for the NOx emission factors of the four-phase RDE tests was 0.90–0.92, indicating that NOx emissions deteriorated linearly with an increase in mileage. Based on the linear fitting results, the NOx emission control of the test vehicles during 700,000 km of on-road driving was highly likely to be qualified. These results can be used by environmental authorities to supervise the NOx emission conformity of in-use HDDVs after validation using other types of vehicles.

Measuring the route topography impact on real driving emissions based on neural network models

Route topography is an important test boundary of real driving emission (RDE) tests. However, the RDE test boundaries, such as atmospheric environment, driver behavior, route topography, and traffic congestion, are random, uncertain, and completely coupled. It is difficult to know to what extent route topography can determine on-road emissions, especially in a region with hilly topography. In this regard, the neural network predictor importance algorithms were proposed to measure the importance of the route topography test boundary. Based on tens of thousands of data window samples from the RDE tests in Chongqing, factor analysis was performed to reduce the data dimensionality and eliminate information overlap, and neural network models were established to predict pollutant emissions and calculate the relative importance of input variables. The results show that route topography is comparable to trip dynamics for on-road emissions but the importance of the route topography test boundary is not fully appreciated in the existing RDE regulation, making mountain cities suffer from severe vehicle emissions that are not effectively controlled.

Investigation of exhaust emissions from the gasoline engine of a light duty vehicle in the Real Driving Emissions test

The article contains the research results and analysis of the processes that take place as part of a gasoline engine light duty vehi-cle Real Driving Emissions test. Dimensionless characteristics of exhaust emission and fuel mass consumption in the RDE test were also determined: emission intensity, particle number emission intensity, fuel mass consumption intensity. An algorithm for determining the characteristics specific distance pollutant emission, specific distance particle number and specific distance fuel mass consumption in the vehicle speed domain in the RDE test was presented using the Monte Carlo method. The determined characteristics were approximated by polynomial functions in the form of sets of points. These relationships were characterized by a large dispersion of values, which was primarily due to the fact that the random values of the averaging limits contain very different engine operating conditions.

Evaluating the Measurement Uncertainty of On-Road NOx Using a Portable Emission Measurement System (PEMS) Based on Real Testing Data in China

An evaluation of the measurement uncertainty of on-road NOx emissions using portable emission measurement system (PEMS) based on real local testing data collected in China was carried out as per the type B method defined in the EN 17507 standard. The aim of this work was to quantify the “absolute” measurement uncertainty of PEMSs, which excluded “PEMS relative to laboratory constant volume sampler (CVS)” uncertainty from the calculation of on-road NOx measurement uncertainty using PEMSs. PEMS instruments from three mainstream manufacturers were employed. The zero drift of the NOx analyzers was evaluated periodically during the real driving emissions (RDE) test, and it was noticed that there was neither a linear nor step model of zero drift, with no correlation with the boundary conditions or measurement principle. Additionally, from the 256 valid RDE tests, the zero drift always ranged from 3.8 ppm to −3.8 ppm, and more than 95% of the span drifts were within a range of 1.5%. Based on the laboratory testing of ten vehicles using the worldwide harmonized light-duty vehicle test cycle (WLTC), the type B uncertainty of PEMS NOx measurements corresponding to China-6a and China-6b limits was assessed. An uncertainty of 26.5% for China-6a was found (NOx limit = 60 mg/km over the WLTC), which is very close to the 22.5% from the EU evaluation results (NOx limit = 80 mg/km over the WLTC); the uncertainty with respect to China-6b was found to be 42.8% because the type-I limit was tuned down to 35 mg/km. This result indicates that, with the ever-tightening regulatory limits of vehicle NOx emissions, big challenges will be posed in terms of the reliability of PEMS measurements, which requires PEMS manufacturers to improve the performance of the instruments and policymakers to refine the test procedures and/or result calculation method to minimize the impacts.

Comparison of Gasoline Engine Exhaust Emissions of a Passenger Car through the WLTC and RDE Type Approval Tests

The article presents a comparison of exhaust emission test results from a passenger car with a spark-ignition engine examined with the WLTC (Worldwide Harmonized Light-Duty Vehicles Test Cycle) test, which was carried out on a chassis dynamometer, and examined with a RDE (Real Driving Emissions) test, which was conducted in real vehicle operating conditions. The exhaust emissions and the emitted particle number in the individual phases of both tests were determined. Large disparities were found in the results of the two tests. The cold start-up had a particularly significant impact on the test results in the case of the WLTC test. This impact is much greater than in the RDE test, mainly due to the fact that the RDE test is much longer than the WLTC test. Moreover, the engine load in the RDE test was greater than in the WLTC test. As a result of the conducted analyses, it was postulated that the research should be continued in stochastic conditions for the vehicle speed function, e.g., in the implementation of the speed function determined for the real conditions of the vehicle operation.

Are we getting vehicle emissions estimation right?

Simulation is a valuable prediction tool to evaluate the impact of climate change interventions prior to disruptive implementations that may yield unintended and unwanted consequences. Advances in agent-based simulation allow us to estimate the dynamic emissions produced by vehicles at a fine resolution, with each vehicle modelled individually. The scalability of these models allow decision-makers to evaluate large-scale scenarios. But how good are these models? In this paper, the authors apply a state-of-the-art emissions model in the Multi Agent Transport Simulation (MATSim) framework to simulate individual vehicle emissions. Simulation results are compared with real driving emissions tests, using a portable emissions measurement device on a light and heavy vehicle. Quantifying the gap between macro-level simulation and actual emissions, the paper contributes by showing that pollutants are significantly underestimated, especially for heavy vehicles. This confirms prior micro-scale studies and magnifies the detrimental impact of using uncorrected aggregated models to inform environmental policy affecting transport. • Quantifying the gap in emission estimates on large-scale traffic simulations. • City-scale activity-based transport model coupled with vehicle-specific emissions. • Variation in real driving emissions is much larger than in randomised simulations. • Macro-level models underestimate heavy vehicle emissions more than light vehicles.