Fleet Test Research Articles

Engine Oil Degradation in the Real-World Bus Fleet Test Based on Two Consecutive Operational Intervals

The literature on the subject and the results of numerous research experiments indicate that single replacement cycles do not reflect the actual state of oil quality in the context of its degradation. Monitoring the operational quality of the oil in several successive stages allows for a more accurate diagnosis of the optimal oil change time. Therefore, it was decided to investigate the relationship between two consecutive periods of changing the operating oil in an engine. Comparative tests of seven buses included in the fleet were carried out. An important division criterion was taken into account—the operation of city and intercity buses. The HDXRF instrumental chemical analysis method was used to determine changes in the content of abrasive metals, and additives in engine oils. Additionally, the oxidation, nitration, sulfonation, and soot content were assessed using infrared spectroscopy (FTIR) based on the ASTM E2414-10 standard and kinematic viscosity at 40 °C and 100 °C using a Stabinger viscometer according to ASTM D7042. The course of these changes was analyzed in terms of their dynamics. The comparative study aimed to identify trends and sources of differences between the tested oils, as well as to demonstrate the number of exceedances of limit values for the selected parameters.

Endurance results of a refuels fleet test in a real application based on directly comparable truck test pairs

Synthetic fuels from a renewable base are an essential part of a greenhouse gas-neutral mobility, especially in transport sector. While scaling production of e-fuels (fuels based on electrolysis hydrogen) is ongoing, HVO called paraffinic diesel fuels are already available. Their production is based on the hydrogenation of waste and residues and they are established as diesel substitute in several applications. With regard to the approval of these fuels in German regulation, the question repeatedly arises as to whether they can be used easily and what effects can be achieved. This article describes an application in a real logistics application, in which both the everyday use and the concrete comparability to a refueling with conventional gas station diesel were ensured. The use of several parallel active and different truck pairs has shown that the use of HVO in existing vehicles has achieved the desired CO2 reduction. A detailed analysis of the engine oil also showed that no undesirable effects could be observed here either. From the perspective of this project, HVO fuels are ready for use for a significant greenhouse gas reduction in logistics.

A Vehicle Fleet Study to Investigate the Effect of B20 and B10 Usage on Engine Oil Degradation

The use of blended palm biodiesel has been implemented in Malaysia starting with B5 (5% palm biodiesel blended with 95% petroleum diesel) in 2011, B7 (7% palm biodiesel blended with 93% petroleum diesel) in 2014, and B10 in 2019. Palm biodiesel has been regarded as a reliable petroleum diesel substitute since 1995 following the research and development carried out by MPOB. Six trucks participated in the trial to evaluate the use of B20 and B10 through fleet testing and laboratory investigations. The trucks were divided into two groups according to fuel used. The field trial started in 2019 and ended in 2021. Engine oil and filter samples were taken at 5,000 kilometers intervals between service interval 30,000 kilometers. All the engine oil samples were within their operational service limits at each 5,000 kilometers sampling interval. The average viscosities of used engine oil in B20 group were 12.75 mm2 s-1 and for B10 group 12.98 mm2 s-1. The total basic number (TBN) values for the B20 group was 6.4 mg KOH g-1 and 6.3 mg KOH g-1 on average for B10 group. The wear and contaminants test showed the average iron particles concentrations for B20 and B10 groups were 22 ppm and 25 ppm respectively. In terms of engine oil evaporation, the average zinc and phosphorus concentrations reduced by only 20% for both vehicle groups. The average values for soot in oil showed that the B20 group had 10% less soot build-up compared to B10 group. The use of B20 had affected engine oil quality with minimal advantages for soot in oil and iron particle concentrations.

Current vehicle emission standards will not mitigate climate change or improve air quality

The vehicle emissions testing programme was conducted by the UK Department of Transport in 2016 in response to emissions tampering exposed in the Volkswagen (VW) emissions scandal. The programme identified large emissions discrepancies between real-world and in-lab testing across a range of Euro 5 and Euro 6 diesel passenger vehicles. The large vehicle test fleet reflects the current challenges faced in controlling vehicle emissions. This paper presents the following findings: NOx emissions are altered due to exhaust gas recirculation mismanagement. A new Real-Life Emissions methodology is introduced to improve upon the current Real Driving Emissions standard. A large and concerning emissions divergence was discovered between the achieved NOx improvement and deterioration of CO2. The findings act as catalysts to improve vehicle emissions testing beyond standards established since the VW scandal, aiding in the development of better climate change mitigation strategies and bring tangible air quality improvements to the environment.

Energy audit and carbon footprint in trawl fisheries

The combustion of fossil fuels is considered a major cause of climate change, which is why the reduction of emissions has become a key goal of the Paris climate agreement. Coherent monitoring of the energy profile of fishing vessels through an energy audit can effectively identify sources of inefficiency, allowing for the deployment of well-informed and cost-efficient remedial interventions. We applied energy audits to a test fleet of ten vessels, representing three typical Mediterranean trawl fisheries: midwater pair trawl, bottom otter trawl, and Rapido beam trawl. Overall, these fisheries use approximately 2.9 litres of fuel per kilogram of landed fish, but the fuel consumption rate varies widely according to gear type and vessel size. This amount of fuel burned from capture to landing generates approximately 7.6 kg∙CO2/kg fish on average. Minimising impacts and energy consumption throughout the product chain may be another essential element needed to reduce the environmental costs of fishing. Our results provided a set of recognised benchmarks that can be used for monitoring progress in this field.

Autonomous Vehicle Accident Data Analysis: California OL 316 Reports: 2015–2020

Abstract Six years (2015–2020) of autonomous vehicle (AV Level 3) crash data from California's (CA) OL 316 collision reports of AV crashes while in the autonomous mode (AM) or disengaged from AM just before the collision, divided by the associated CA AV make and mileage driven in the AM, are compared with the University of Michigan Transportation Research Institute (UMTRI) corrected human driver crash frequency. AV test drivers in CA mandatorily self-report every crash, whereas average drivers underreport minor accidents, so the UMTRI reporting correction factor permits comparison. CA's AV AM mileage is only a few million miles over the last few years, with virtually no police-reported crash data yet available. OL 316 crash consequence data (e.g., damage, injuries, etc.) is anecdotal and inconsistently self-reported. The CA collision report data indicate the CA AV test fleet exhibits multiples of the human crash frequency. Invariably, the AV accidents are the human driver's fault, with a majority being rear collisions. The human drivers appear less able to anticipate the AV's more conservative driving. CA's AV experience predicts more widespread deployment of existing AV technologies is not likely to reduce vehicle crash frequency, at least in the short term, and might well increase it.

Quantification of Exposure to Black Carbon and NOx inside Vehicles when Driving through a Road Tunnel

This study aimed to quantify the concentrations of NOx and black carbon (BC) inside vehicle cabin in relation to outside concentrations while driving through a 3.8 km long road tunnel, Sodra Lanken, in Stockholm. 10 different vehicles of different types, brands and sizes were chosen as the test fleet. Every vehicle was run back and forth 8 times through the road tunnel, four times in each direction. Temperature inside vehicles was set to 20°C and fan speed was set to auto. The instruments for measuring NOx were two model 405 nm NO2/NO/NOx Monitor™ from 2B technologies, and BC was measured using two Aethalometer, microAeth® model AE51 from AethLabs. In addition, CO2 was also measured using Senseair K33 LP T/RH CO2-sensor. All instruments were battery powered. From the speed of which the pollutants decreased after exiting the tunnel, turnover time for the air in the tested vehicles was calculated to be between 1 and 2 minutes. One passage through the tunnel took about 4 minutes. The total exposure in the passenger compartment varied depending on the car model. The measurements of BC showed that a driver is exposed to between 20% and 80% of the exposure compared driving in a roofdown convertible through the tunnel. For NOx, the exposure in the car compartment was significantly higher, and almost no difference compared to driving with the roof down. Approximately 20%–40% of the BC exposure occurred after the vehicles had exited the tunnel. For NOx, about 30%-45% of the inside car exposure occurred outside the tunnel. The BC to NOx ratio inside the tunnel was calculated to 12.2 ± 1.1 mg BC g-1 NOx-1. Compared to the corresponding ratio in the emission model HBEFA 4.0, which is is 4.3 mg BC g-1 NOx-1, the measured ratio was three times higher.

Research on the adaptability of vehicles with different technical types to the China 6 regulation standard

A test fleet including 47 gasoline vehicles with 6 different technical types was organized, and the adaptability of these vehicles under China 6 standard was studied. By analyzing the performance of the vehicles tested in laboratory and in real-world, technical types that could simultaneously reconcile emission and fuel consumption performance were proposed. The results show that all vehicles were well performed under laboratory conditions, but in real-world conditions, 50% direct injection vehicles without GPF would fail the RDE test. On the other hand, vehicles with GPF had better performance, all of which passed the RDE tests even if the conformity factor decreased from 2.1 to 1. In addition, it is found that the fuel consumption of the DI vehicles were lower than that of the PFI vehicles. As the DI vehicles with GPF showed better performance on the balance of emission and fuel consumption, indicating that they may have better potentials to deal with the increasing tightened emission and fuel consumption standards at the same time.

Vehicular fuel consumption estimation using real-world measures through cascaded machine learning modeling

Many of the existing studies on vehicular fuel consumption estimation are criticized in aspects such as ignoring real-world training data, low diversity of test fleet, impracticality of models in real-world applications (i.e. instrument-independent eco-driving), or their prediction power in the non-linear multi-dimensional space of fuel consumption estimation. In this paper, we proposed a machine learning modeling method using large on-road data collected from a fleet of 27 vehicles. The usability of models in absence of specialized instruments was in focus. We tried to improve the accuracy of our base models by introducing engine-speed estimates through a cascaded modeling procedure. As a result, the accuracy of models reached 83%, while improvements as high as 37% were achieved depending on the technique (support vector regression or artificial neural networks) and vehicle class. Finally, we took the first step from vehicle-specific models towards category-specific modeling by a categorical analysis over fleet attributes.

Nanoemulsion Fuel Additive Used as a Diesel Combustion Catalyst

This research article discloses how a uniquely structured fuel additive can easily be mixed with commercially available diesel fuel to produce an extremely stable nanoemulsion fuel. Even when using an ultralow dose (125 ppm), the additive still creates a large and catalytically active surface area using billions of nanosized water droplets (4 nanometers). No metallic or organometallic compounds were used. When used in heavy duty diesel engines, treated fuel significantly improves vehicle fuel economy. Extensive verification testing was carried out using multiple fleets of heavy duty diesel trucks operating for up to two years under “real-world” driving conditions. Testing used 538 heavy duty trucks and 15 different vehicle fleets. Test vehicles used 475,000 litres of treated fuel and covered a total of 14 million kilometres. Fleet testing was supervised by one of the premier European testing agencies (TNO Quality Services BV). Raw fuel economy data was collected and analyzed by an independent consulting agency andd showed a combined average weighted fuel savings of 9.7%. Diesel engine CO2 emissions are one of the many contributory causes of global warming. Unfortunately, new engine fuel economy technologies can take 10 years to have a 50% impact (typically 5% per year, as older vehicles are slowly replaced with new models). However, using the additive would immediately improve the combustion properties of fuel being used in these vehicles with the potential to reach up to 90% of the entire diesel vehicle population within about 60 days.

Evaluating the In-Service Emissions of High-Mileage Dedicated Methanol-Fueled Passenger Cars: Regulated and Unregulated Emissions

This paper reports the regulated, unregulated, and particle number emissions from six high-mileage, China-4 compliant, dedicated methanol taxis over the new European driving cycle. Compared to new vehicles, carbon monoxide, total hydrocarbons, and nitrogen oxides emissions from in-use methanol taxis increased by 76.1%, 40.2%, and 179.8%, respectively. Still, they managed to meet China-4, indicating good in-service conformity. In the test fleet, the test vehicles with longer mileage inclined to emit higher carbon monoxide and total hydrocarbons emissions. Formaldehyde emissions from these field-aged taxis ranged from 1.06 to 2.33 mg/km, which were similar to or lower than those from previously reported pre-Euro-5 gasoline vehicles. One of the six test vehicles produced extraordinarily high unburned methanol emissions, which was about ten times higher than the rest of the properly operating vehicles due to possible misfire, suggesting that unburned methanol will be the primary stress for future methanol applications. Compared to the regulated emissions, formaldehyde and unburned methanol emissions deteriorated at faster rates along with catalyst aging. Particle number emissions from these methanol taxis remained low even after high-mileage driving, suggesting the compatibility of methanol fueling in future particle number compliance.

High-throughput growth and data with ‘impact’: Converting the Singer testing fleet into a lab

Singer Instruments have been embedded in the yeast academic community since 1982, and had supported the wider scientific community for 85 years. Traditionally, the role of our lab has been testing prototypes, engaging in the work of R&D for the production and improvement of robotic products. For the first time, in collaboration with the University of Manchester, Singer have recruited a PhD student to actively engaged in independent research. This has required quickly changing tack from a prototype and software development test bed, to a lab capable of outputting meaningful data to collaborators within the Aromagenesis project. Collaboration with local beverage producers has allowed a transitional generation of impactful data, that is in the process of informing experimentation into their own brewing processes. Colonies are picked using the newly developed PIXL, and strains arrayed via the ROTOR in excess of 1536 colonies per plate, colony growth data was analysed using the imaging device PhenoBooth. This has allowed rapid generation of data on numerous media types in the projects relatively short time span. The effects of in-house research are already been realised, with innovative changes to products, and detailed requests for making software more helpful to scientists. With a greater automation capacity than is currently required by our own research, the ability to engage in collaborative projects and for Singer to provide a service to the yeast research community is very much increasing.

How much energy does a car need on the road?

A car often requires more energy when driven in daily operation than indicated by the manufacturer. This paper presents a model to derive this real-world energy demand for a passenger car, based on a few widely available input data on vehicle operation. The approach works for conventional and alternative propulsion technologies. The underlying data stem from an extensive Swiss chassis dynamometer and on-road measurement campaign, which lasted for more than a year. The test fleet consisted of a compressed natural gas, gasoline hybrid, gasoline plug-in hybrid, fuel cell electric, and a battery-electric vehicle. The derived model adjusts the propulsive power demand within the legislative WLTP cycle for class 3b vehicles to a road mission by incorporating effects of traffic, driving styles, and topography. It additionally accounts for load from auxiliary devices. The approach works with input data from a household travel survey or traffic flow simulation and can serve as a tool to everyone who needs to estimate the average on-road energy demand of any passenger car or a fleet of them, rather than their type-approval values. Tested on a compact-sized vehicle, the approach estimates a mean discrepancy in real-world energy demand to WLTP type-approval values for Switzerland of about 22% for conventional cars. Furthermore, we can show similar gaps for hybrid technologies of around 30% and for battery-electric cars of 25%.

Requirements for Electric Machine Design based on Operating Points from Real Driving Data in Cities

Increasing environmental awareness leads to the necessity for more efficient powertrains in the future. However, the development of new vehicle concepts generates a trend towards ever shorter development cycles. Therefore, new concepts must be tested and validated at an early stage in order to meet the increasing time pressure. This requires the determination of real driving data in fleet tests in order to generate realistic driving cycles, which correspond as closely as possible to the actual driving behavior of the applications use case. Within the scope of this paper, real driving data are analyzed and used to create a representative driving cycle. The resulting driving cycle based on real driving characteristics is then used to investigate the impact of application-based design for powertrains on the design of electric machines, by illustrating the difference between synthetic operating points and real driving data.

Impacts of gasoline aromatic and ethanol levels on the emissions from GDI vehicles: Part 1. Influence on regulated and gaseous toxic pollutants

Gasoline composition is critical to the formation of regulated emissions and gaseous toxic pollutants from spark ignition engines equipped with direct injection fueling. This study investigated the impacts of varying aromatic and ethanol levels on the exhaust emissions of five gasoline direct injection (GDI) vehicles. A total of eight fuels were used, with aromatic levels of 20% and 30% by volume, and ethanol levels ranging from 0% to 20% by volume. The test fleet consisted of 2016 to 2017 model year Tier 3 vehicles operated over the LA92 drive cycle. We showed that total aromatics played an important role for the emissions of non-methane hydrocarbons (NMHC), total hydrocarbons (THC), formaldehyde, and mono-aromatic hydrocarbon species (i.e., benzene, toluene, ethylbenzene, and xylenes), with an increase of gasoline aromatics resulting in higher emissions of these pollutants. Increasing ethanol levels in gasoline led to statistically significant reductions in carbon monoxide (CO) and statistically significant increases in acetaldehyde emissions. Emissions of nitrogen oxides (NOx) were not significantly affected by either aromatics or ethanol levels across the fleet. There was a lack of strong trends between the fuels in the ozone forming potential (OFP). The largest contribution to OFP in the exhaust was from aromatic species, followed by alkenes and alkanes. Overall, aromatics played a more dominant role in emissions formation than ethanol content, indicating multiple formation pathways for these pollutants.

Detailed Speciation of Intermediate Volatility and Semivolatile Organic Compound Emissions from Gasoline Vehicles: Effects of Cold-Starts and Implications for Secondary Organic Aerosol Formation.

Over the past two decades vehicle emission standards in the United States have been dramatically tightened with the goal of reducing urban air pollution. Secondary organic aerosol (SOA) is the dominant contributor to urban organic aerosol. Experiments were conducted at the California Air Resources Board Haagen-Smit Laboratory to characterize exhaust organics from 20 gasoline vehicles recruited from the California in-use fleet. The vehicles spanned a wide range of emission certification standards. We comprehensively characterized intermediate volatility and semivolatile organic compound emissions using thermal desorption two-dimensional gas-chromatography-mass-spectrometry with electron impact (GC × GC-EI-MS) and vacuum-ultraviolet (GC × GC-VUV-MS) ionization. Single-ring aromatic compounds with unsaturated C4 and C5 substituents contribute a large fraction of the intermediate volatility organic compound (IVOC) emissions in gasoline vehicle exhaust. The analyses of quartz filters used in GC × GC-VUV-MS show that primary organic aerosol emissions were dominated by motor oil. We combined our new emissions data with published SOA yield parametrizations to estimate SOA formation potential. After 24 h of oxidation, IVOC emissions contributed 45% of SOA formation; BTEX compounds (benzene, toluene, xylenes, and ethylbenzene),40%; other VOC aromatics, 15%. The composition of IVOC emissions was consistent across the test fleet, suggesting that future reductions in vehicular emissions will continue to reduce SOA formation and ambient particulate mass levels.

Comparison of Battery Degradations Induced By Different Synthetic Driving Cycles and Real-World Traffic Conditions

Advances in lithium ion battery pack technology have led to significant market penetration for electric vehicles (EVs), but there is still a need to develop new battery technologies, better control algorithms, and faster charging strategies to enhance further the ownership experience. Once developed, these advances must be validated. Unfortunately, fleet testing is not often an option because of the associated cost. To address this issue and permit the validation of new technologies in the laboratory quickly, many studies are relying on synthetic driving cycles to mimic the usage cells would experience under actual utilization. Among the more popular ones are the Federal Urban Driving Schedule (FUDS), a US standard; the Dynamic Stress Test (DST) which is a simplified version of the FUDS cycle; and the New European Driving Cycle (NEDC), a European standard. The ability of these cycles to replicate EV usage is usually taken for granted; whereas, to the best of our knowledge, no study has scrutinized these cycles to establish if the induced degradation is indeed comparable with what is observed from real driving data. It is proposed here to investigate the impact of the most-used, standardized driving cycles on state-of-the art lithium-ion cells and evaluate them against the impact of real driving in a laboratory-controlled environment. Different analysis techniques and metrics, such as voltage response, capacity, rate capability, and resistance, are employed to compare the most common synthetic driving cycles (FUDS, DST and NEDC) with scaled-down real driving data selected from the Hawai'i Natural Energy Institute (HNEI) in-house database. Two different sets of real driving data was used, one using a single commute in a loop and one using 25 similar commutes in a loop, to reveal any effect of traffic. This study aimed to elucidate any significant discrepancies between simulated and real driving outcomes, determine the effect of traffic conditions, and propose possible improvements.

TBN performance study on a test fleet in real-world driving conditions using present-day engine oils

The article describes the processes of degradation of five engine oils available from various manufacturers, but belonging to the same SAE viscosity grade. The direction and intensity of changes in Total Base Number (TBN) have been analysed. As part of the experiment, the changes in engine oils occurring during actual operation (under conditions which can be described as “harsh”, i.e. frequent starting of the engine, short distance driving, extended engine idling) have been observed. All engine oils were operated in passenger cars of a uniform fleet of 25 vehicles. Total Base Number was determined in accordance with the test method ASTM D2896. The obtained results have led to the development of a statistical model enabling to calculate average predictive values of TBN for a given mileage. Moreover, an evaluation of a FTIR spectrum of an engine oil sample was presented. For the used engine oil differentiation process, FTIR spectra were analysed in the regions 600–2000cm−1 and 3600–3700cm−1 for five oil sample (one from each group). The results may facilitate decision-making regarding the service life of engine oils.

Evaluation of emission factors for light-duty gasoline vehicles based on chassis dynamometer and tunnel studies in Shanghai, China

CO, THC, NOx, and PM emission factors of 51 light-duty gasoline vehicles (LDGVs) spanning the emission standards from Euro 2 to Euro 5 were measured by a chassis dynamometer. High frequencies of high-emitting vehicles were observed in Euro 2 and Euro 3 LDGV fleet. 56% and 33% of high-emitting vehicles contributed 81%–92% and 82%–85% of the emissions in Euro 2 and Euro 3 test fleet, respectively. Malfunctions of catalytic convertors after high strength use are the main cause of the high emissions. Continuous monitoring of a gasoline vehicle dominated tunnel in Shanghai, China was conducted to evaluate the average emission factors of vehicles in real-world. The results indicated that the emission factors of LDGVs were considerably underestimated in EI guidebook in China. The overlook of high-emitting vehicles in older vehicle fleet is the main reason for this underestimation. Enhancing the supervision of high emission vehicles and strengthening the compliance tests of in-use vehicles are essential measures to control the emissions of in-use gasoline vehicles at the present stage in China.

Comparison of Gasoline Direct-Injection (GDI) and Port Fuel Injection (PFI) Vehicle Emissions: Emission Certification Standards, Cold-Start, Secondary Organic Aerosol Formation Potential, and Potential Climate Impacts.

Recent increases in the Corporate Average Fuel Economy standards have led to widespread adoption of vehicles equipped with gasoline direct-injection (GDI) engines. Changes in engine technologies can alter emissions. To quantify these effects, we measured gas- and particle-phase emissions from 82 light-duty gasoline vehicles recruited from the California in-use fleet tested on a chassis dynamometer using the cold-start unified cycle. The fleet included 15 GDI vehicles, including 8 GDIs certified to the most-stringent emissions standard, superultra-low-emission vehicles (SULEV). We quantified the effects of engine technology, emission certification standards, and cold-start on emissions. For vehicles certified to the same emissions standard, there is no statistical difference of regulated gas-phase pollutant emissions between PFIs and GDIs. However, GDIs had, on average, a factor of 2 higher particulate matter (PM) mass emissions than PFIs due to higher elemental carbon (EC) emissions. SULEV certified GDIs have a factor of 2 lower PM mass emissions than GDIs certified as ultralow-emission vehicles (3.0 ± 1.1 versus 6.3 ± 1.1 mg/mi), suggesting improvements in engine design and calibration. Comprehensive organic speciation revealed no statistically significant differences in the composition of the volatile organic compounds emissions between PFI and GDIs, including benzene, toluene, ethylbenzene, and xylenes (BTEX). Therefore, the secondary organic aerosol and ozone formation potential of the exhaust does not depend on engine technology. Cold-start contributes a larger fraction of the total unified cycle emissions for vehicles meeting more-stringent emission standards. Organic gas emissions were the most sensitive to cold-start compared to the other pollutants tested here. There were no statistically significant differences in the effects of cold-start on GDIs and PFIs. For our test fleet, the measured 14.5% decrease in CO2 emissions from GDIs was much greater than the potential climate forcing associated with higher black carbon emissions. Thus, switching from PFI to GDI vehicles will likely lead to a reduction in net global warming.