Real-world emissions and fuel consumption of gasoline and hybrid light duty vehicles under local and regulatory drive cycles

Review of Energy Management Methods for Fuel Cell Vehicles: From the Perspective of Driving Cycle Information

Energy management methods (EMMs) utilizing sensing, communication, and networking technologies appear to be one of the most promising directions for energy saving and environmental protection of fuel cell vehicles (FCVs). In real-world driving situations, EMMs based on driving cycle information are critical for FCVs and have been extensively studied. The collection and processing of driving cycle information is a fundamental and critical work that cannot be separated from sensors, global positioning system (GPS), vehicle-to-vehicle (V2V), vehicle-to-everything (V2X), intelligent transportation system (ITS) and some processing algorithms. However, no reviews have comprehensively summarized the EMMs for FCVs from the perspective of driving cycle information. Motivated by the literature gap, this paper provides a state-of-the-art understanding of EMMs for FCVs from the perspective of driving cycle information, including a detailed description for driving cycle information analysis, and a comprehensive summary of the latest EMMs for FCVs, with a focus on EMMs based on driving pattern recognition (DPR) and driving characteristic prediction (DCP). Based on the above analysis, an in-depth presentation of the highlights and prospects is provided for the realization of high-performance EMMs for FCVs in real-world driving situations. This paper aims at helping the relevant researchers develop suitable and efficient EMMs for FCVs using driving cycle information.

Impacts on real-world extra cold start emissions: Fuel injection, powertrain, aftertreatment and ambient temperature

Vehicles emit substantial amounts of pollutants during start periods. Engine starts mainly occur in urban areas, causing serious harm to humans. To investigate the impacts on extra cold start emissions (ECSEs), eleven China 6 vehicles with various control technologies (fuel injection, powertrain, and aftertreatment) were monitored with a portable emission measurement system (PEMS) at different temperatures. For conventional internal combustion engine vehicles (ICEVs), the average ECSEs of CO₂ increased by 24%, while the average ECSEs of NOx and particle number (PN) decreased by 38% and 39%, respectively, with air conditioning (AC) on. Gasoline direct injection (GDI) vehicles had 5% lower CO₂ ECSEs, but 261% higher NOx ECSEs and 318% higher PN ECSEs than port fuel injection (PFI) vehicles at 23 °C. The average PN ECSEs were significantly reduced by gasoline particle filters (GPFs). The GPF filtration efficiency was higher in GDI than PFI vehicles due to particle size distribution. Hybrid electric vehicles (HEVs) generated excessive PN extra start emissions (ESEs), resulting in a 518% increase compared to ICEVs. The start times of the GDI-engine HEV accounted for 11% of the whole test time, but the proportion of PN ESEs relative to total emissions were 23%. Linear simulation based on the decrease in ECSEs with increasing temperature underestimated the PN ECSEs from PFI and GDI vehicles by 39% and 21%, respectively. For ICEVs, CO ECSEs varied with temperature in a U shape with a minimum at 27 °C; NOx ECSEs decreased as ambient temperature increased; PFI vehicles generated more PN ECSEs at 32 °C than GDI vehicles, stressing the significance of ECSEs at high temperature. These results are useful for improving emission models and assessing air pollution exposure in urban aeras.

Emission characteristics and light absorption apportionment of carbonaceous aerosols: A tunnel test conducted in an urban with fully enclosed use of E10 petrol

To reduce the heavy dependence on petroleum, bioethanol has been increasingly employed as an alternative and sustainable transportation fuel. However, the characteristics of black carbon (BC) emissions from E10 petrol vehicles (i.e., ethanol-gasoline containing 10% ethanol) are still unclear, especially under real driving conditions. Here, a tunnel test was conducted during a cold winter. This tunnel was characterized by heavy traffic comprising more than 98% E10-fueled gasoline vehicles (GVs). Real-time BC concentrations, traffic parameters and meteorological conditions were recorded during the sampling campaign. The average BC concentration inside the tunnel (10.94 ± 5.02 μg m^-3) was almost twice the background concentration. Based on aethalometer AE33 in situ measurements and the minimum R-squared (MRS) method, real-time aerosol light absorption was apportioned. The light absorption proportions of BC, primary brown carbon (BrC₁) and secondary brown carbon (BrC₂) were 79.86%, 2.78% and 17.36%, respectively, at 370 nm. The BC emission factor (EF_BC) of the E10-fueled vehicles was 1.09 ± 0.49 mg km^-1·veh^-1 and 15.24 ± 6.85 mg·(kg fuel)^-1, lower than those of traditional gasoline fueled vehicles in previous studies. This study can support the compilation of vehicular BC emission inventories, provide recommendations for biofuel policies and contribute to comprehensively understanding the climatic impact of E10 petrol.

Developing and analyzing eco-driving strategies for on-road emission reduction in urban transport systems - A VR-enabled digital-twin approach

A vast number of pollutants are generated from on-road commuting vehicles, and there is an increasing need to explore vehicle emission monitoring and mitigation strategies. Traditionally, vehicle emissions can be monitored and measured directly from on-vehicle devices such as a sensor at the tailpipe, or based on expensive data collection tools such as roadside units; while another mainstream research estimates vehicle emissions by relying on the connection to the vehicle motions, which can approximately calculate vehicle emissions under certain traffic conditions. This paper proposes a virtual reality (VR) enabled digital twin platform for on-road emission monitoring, and it develops and evaluates eco-driving strategies within a specific area. The proposed approach, integrating a VR-based digital environment, a micro-simulation model for background traffic, and a Motor Vehicle Emission Simulator for emission estimation, offers an alternative to collect and examine vehicle emissions such as NOx under various traffic conditions. A case study on a central business area in Melbourne is conducted and eco-driving strategies are tested in two scenarios. The first scenario concerns the impact of hybrid electric vehicles and connected autonomous vehicles, which points to the long-term benefit of having controllable and cleaner modes of transportation as a strategy. Results showed that manipulating the penetration rate of emission-friendly engines or motions could reduce vehicle emissions effectively. The second scenario concerns the real-time eco-routing based on emission-optimum, which points to the short-term benefit of emission control strategies. Human-in-the-loop experiments were conducted to test drivers' responses toward routing options. Results showed that over 90% of participants would follow the eco-routing recommendations completely. The presented study offers an alternative to data-generating, analyzing, and managing approaches for on-road emissions in urban transportation systems.

Developing an optimal sampling design to monitor the vehicle fuel consumption gap

Monitoring the fuel consumption gap between official and real-world measurements is of great interest to policy makers and researchers. This study explores how sampling methods (simple random, stratified and quota sampling) can be used to supplement and validate the monitoring. Three user datasets were utilised to simulate the fuel consumption gap of the 11.6-15.5 million vehicles registered annually in the European Union (2018-2020). Results suggest that a simple random sample of 16,240 vehicles is sufficient to estimate accurately the fleets' average fuel consumption gap. Stratified sampling can reduce the sample size to less than 4,500 vehicles. To estimate accurately the fuel consumption gap of each manufacturer, the sample size increases to approximately 17,200 vehicles. The increase in sales of plug-in hybrid vehicles in 2020 led to an increase of the average fuel consumption gap by 8% and its standard deviation (variability) by 20%. This higher variability resulted in a more than double sample size, compared to previous years. It was also found that the introduction of the Worldwide Harmonized Light vehicles Test Procedure (WLTP) reduced the average gap by 20-24%. This study highlights the viability of a sampling scheme to estimate the fuel consumption gap by monitoring less than 0.05% of the fleet. Moreover the study draws attention to the need for further analysis and understanding of the real-world use and fuel consumption of plug-in hybrid vehicles.

Effective and Acceptable Eco-Driving Guidance for Human-Driving Vehicles: A Review

Eco-driving guidance refers to courses, warnings, or suggestions provided to human drivers to improve driving behaviour to enable less energy use and emissions. This paper reviews existing eco-driving guidance studies and identifies challenges to tackle in the future. We summarize two categories of current guidance systems, static and dynamic, distinguished by whether real-world driving records are used to generate behaviour guidance or not. We find that influencing factors, such as the content of suggestions, the display methods, and drivers’ socio-demographic characteristics, have varied effects on the guidance results across studies. Drivers are reported to have basic eco-driving knowledge, while the question of how to motivate the acceptance and practice of such behaviour, especially in the long term, is overlooked. Adaptive driving suggestions based on drivers’ individual habits can improve the effectiveness and acceptance while this field is under investigation. In-vehicle assistance presents potential safety issues, and visualized in-vehicle assistance is reported to be most distractive. Given existing studies focusing on the operational level, a common agreement on the guidance design and associated influencing factors has yet to be reached. Research on the systematic and tactical design of eco-driving guidance and in-vehicle interaction is advised.

Life cycle assessment study on the public transport bus fleet electrification in the context of sustainable urban development strategy

In this paper, the Life Cycle Assessment (LCA) method was applied to investigate the environmental impact of the electrification of the urban bus fleet. Public bus transport in large urban agglomerations is one of the main sources of pollution. To reduce the generation of pollution, electrification of the bus fleet is considered as one of the potential solutions. The authors developed three models of buses with different power units: diesel bus, diesel hybrid bus, and electric bus. The impacts of model buses were analysed at the stage of their production and operation in the city, as well as the impact of diesel fuel and electricity production. Furthermore, a case study was conducted based on the example of the Polish city of Krakow, demonstrating three possible scenarios for the electrification of the urban bus fleet. Moreover, an analysis of the environmental impact of the current and future Polish national energy production system until 2040 was carried out. Using the IMPACT 2002+ Life Cycle Impact Assessment (LCIA) method, the results were reported in four damage endpoint categories: human health, ecosystem quality, climate change, and resources. It was shown that increasing the share of electric buses in urban fleets can be highly beneficial in all four categories if the electricity used to power the electric buses is produced from enough low- and zero-emission energy sources. In addition, the level of environmental burden generated by the different phases of the life cycle of the bus was characterised. Overall, the advantages and possible problems of urban bus fleet electrification were highlighted, and recommendations for future sustainable development strategies were suggested. Thus, this study can be useful as an algorithm to support decision-making related to the electrification of city bus fleets.

Carbon Emission Variations for Plug-In Hybrid Electric Vehicles after Coronavirus Disease 19: An Empirical Case in Chongqing, China

Owing to the lockdowns associated with the Coronavirus Disease 2019(COVID-19) pandemic, carbon emissions were significantly reduced. However, the accurate impacts on the personal transport sector since then remain unclear. To further investigate the influence of sudden public health emergencies on actual carbon emissions from personal electric vehicles, this paper examined the travel patterns and corresponding carbon emissions of plug-in hybrid electric vehicles (PHEVs) operating in Chongqing, China, before and after COVID-19. The results revealed that the pandemic has reshaped the travel patterns of vehicle drivers, with a 9 % reduction in the postpandemic fleet average daily travel mileage. Currently, the total daily carbon emissions of a PHEV with a range of 80 km (PHEV80) are 6.24 kg, which is 13 % lower than emissions from conventional vehicles and 32 % higher than those from electric battery-powered vehicles before the pandemic. Since COVID-19, there has been a 24 % decrease in carbon emissions from PHEV80 vehicles for the fleet and a 30 % maximum increase for individuals. Furthermore, considering the integration of 50 % renewable energy into China’s power grid by 2025, PHEVs can better mitigate the fluctuations in carbon emissions associated with sudden public health emergencies compared with conventional vehicles.