Browse Topic: Greenhouse gas emissions
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
As part of the decarbonisation process for passenger car fleet in Austria, battery electric cars in particular have been subsidised in recent years, as these vehicles are considered to be largely emission free during use and are expected to reduce emissions in future. However, in order to sustainably reduce the global greenhouse gas emissions of Austrian passenger car traffic, taking into account all types of fuel systems, it is necessary to apply a cradle-to-grave approach, as is commonly done in comparable analyses in the literature, which evaluates the emissions of the entire vehicle life cycle. The most important phase in the life cycle assessment remains the well-to-wheel phase, which includes emissions from energy supply and vehicle use. Due to the large number of influencing factors, highly simplified models are usually used for this phase in the literature. As part of this work, a methodology was developed that, allows an in-depth analysis of entire vehicle fleets by linking real vehicle movements with emissions data and energy consumption. By using real vehicle movements, environmental conditions (ambient temperature, etc.) and traffic situations (traffic jams, etc.) can be integrated into the emissions assessment. To capture the influencing factors more realistically, the assessment is performed at hourly rather than annual time intervals, unlike most previous studies. This new approach provides therefore a more detailed and realistic cradle-to-grave analysis of the Austrian passenger car fleet, making it possible to test individual measures in future scenarios and to define a coordinated strategy for minimizing the fleet’s future global greenhouse gas emissions.
Despite remarkable advances in vehicle technology - enhancing comfort, safety, and automation – productivity of transportation over the road continues to decline. Stop-and-go driving remains one of the most persistent inefficiencies in modern mobility systems, leading to greater travel delays, energy waste, emissions, and accident risk. As vehicle volumes rise, these effects compound into systemic challenges, including driver frustration, unstable flow dynamics, and elevated greenhouse gas (GHG) emissions. To address these issues, an extensive data-driven evaluation was performed characterizing the underlying causes of traffic instability and uncovering hidden behavioral parameters influencing traffic flow. This research led to the identification of a previously unrecognized metric - the Driver Comfort Index (DCI) - which quantifies an inter-vehicle spacing behavior that reflects intrinsic human driving behavior. Building on this discovery, mixed traffic is explored to identify its phenomena, where human-driven and machine-controlled vehicles coexist and share the road. It appears that adaptive cruise control (ACC) and connected autonomous vehicles (CAV) are controlled by a non-intrinsic parameter so that traffic mix suffers from a mismatch of vehicle dynamics. This mismatch is explored, and it is proposed to harmonize traffic dynamics by adopting the natural DCI parameter as the single control mechanism. Analytical studies demonstrate that DCI-based traffic flow orchestration, applied integrally to human- and machine-controlled vehicles, enhances traffic flow stability, mitigates stop-and-go oscillations, and significantly improves network efficiency, safety, and environmental performance.
The globe is looking headlong to set up new benchmarks for the reduction of GHG (Green House Gases) considering short-term and long-term strategies. Efforts in the Internal Combustion Engines (ICE) domain have been accelerating to find an alternative way to reduce harmful emissions. Hydrogen is considered as a promising fuel to leapfrog this transition. Hydrogen fuel can be categorized into vast mobility areas viz. ICE and Fuel Cell Electric Vehicle (FCEV). Hydrogen fuel has attracted global attention from engine researchers due to the crude oil crisis and its rise in prices in recent years. This will serve the nation's goal towards carbon neutrality. Hydrogen has a few advantages such as less fueling time, higher heating value and more efficiency making it an eye-touching fuel for the automotive industry. In the contemporary FCEV segment, many fuel cell technologies have evolved, wherein the development of Proton Exchange Membrane (PEM) fuel cell technology has taken a new height for heavy-duty commercial vehicle applications due to its significant interest in the non-existent tailpipe CO2 emissions. Since electric vehicles are also being combined with hydrogen fuel and the opportunity persists to convert it into a hybrid system or FCEV. There is always a keen curiosity of the end user to know the mileage of a vehicle as a distinguishing measure of fuel economy. Thus, it is pertinent to determine the hydrogen fuel economy of the FCEV vehicle. This paper provides an insight into fuel cell fundamentals, the working principle of hydrogen fuel cell vehicles, vehicle operation modes and testing methodology to determine the fuel economy of FCEV based on the electric current method and pressure method. The vehicle (e-Bus) has been validated on a chassis dynamometer based on the prescribed DBDC Cycle in the AIS 049 standard to calculate the hydrogen fuel economy of the FCEV Bus. The multiple stacks of PEM fuel cells connected in series has been used along with the electric powertrain vehicle and estimation of its fuel economy are the focus of this paper.
The US trucking industry heavily relies on the diesel powertrain, and the transition towards zero-emission vehicles, such as battery electric vehicles (BEV) and fuel cell electric vehicles (FCEV), is happening at a slow pace. This makes it difficult for truck manufacturers to meet the Phase 3 Greenhouse Gas standards, which mandate substantial emissions reductions across commercial vehicle classes beginning of 2027. This challenging situation compels manufacturers to further optimize the powertrain to meet stringent emissions requirements, which might not account for customer application specifics may not translate to a better total cost of ownership (TCO) for the customer. This study uses a simulation-based approach to connect customer applications and regulatory categories across various sectors. The goal is to develop a methodology that helps identify the overlap between optimizing for customer applications vs optimizing to meet regulations. To use a data-driven approach, a real-world customer usage pattern analysis was conducted to identify key performance metrics required to optimize driveline components. Additionally, the impact of certification requirements on vehicle performance is examined to ensure compliance while maximizing the benefits of the proposed optimization strategies. The findings of this research will provide valuable insights for manufacturers, enabling the development of trucks that are not only efficient and high-performing but also compliant with environmental standards, ultimately leading to a more sustainable future in the trucking industry.
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