Search Results (59)

Understanding vehicle emissions is essential for developing effective carbon reduction strategies in the transport sector. Conventional emission models often assume homogeneity and linearity, overlooking real-world asymmetries that arise from variations in vehicle design and powertrain configurations. This study explores how machine learning and explainable AI techniques can effectively capture both symmetric and asymmetric emission patterns across different vehicle types, thereby contributing to more sustainable transport planning. Addressing a key gap in the existing literature, the study poses the following question: how do structural and behavioral factors contribute to asymmetric emission responses in internal combustion engine vehicles compared to new energy vehicles? Utilizing a large-scale Spanish vehicle registration dataset, the analysis classifies vehicles by powertrain type and applies five supervised learning algorithms to predict CO₂ emissions. SHapley Additive exPlanations (SHAPs) are employed to identify nonlinear and threshold-based relationships between emissions and vehicle characteristics such as fuel consumption, weight, and height. Among the models tested, the Random Forest algorithm achieves the highest predictive accuracy. The findings reveal critical asymmetries in emission behavior, particularly among hybrid vehicles, which challenge the assumption of uniform policy applicability. This study provides both methodological innovation and practical insights for symmetry-aware emission modeling, offering support for more targeted eco-design and policy decisions that align with long-term sustainability goals. Full article

Hydrogen-powered aircraft constitute a transformative innovation in aviation, motivated by the imperative for sustainable and environmentally friendly transportation solutions. This paper aims to concentrate on the design of hydrogen powertrains employing a system approach to propose representative design models for distribution and propulsion systems. Initially, the requirements for powertrain design are formalized, and a use-case-driven analysis is conducted to determine the functional and physical architectures. Subsequently, for each component pertinent to preliminary design, an analytical model is proposed for multidisciplinary analysis and optimization for powertrain sizing. A double-wall pipe model, incorporating foam and vacuum multi-layer insulation, was developed. The internal and outer pipes sizing were performed in accordance with standards for hydrogen piping design. Valves sizing is also considered in the present study, following current standards and using data available in the literature. Furthermore, models for booster pumps to compensate pressure drop and high-pressure pumps to elevate pressure at the combustion chamber entrance are proposed. Heat exchanger and evaporator models are also included and connected to a burning hydrogen engine in the sizing process. An optimal liner pipe diameter was identified, which minimizes distribution systems weight. We also expect a reduction in engine length and weight while maintaining equivalent thrust. Full article

As global concerns about climate change and air quality intensify, nations are increasingly adopting sustainable transportation solutions, with electromobility emerging as a key alternative. This study investigates the factors influencing powertrain technology choice and the barriers to electric vehicle (EV) adoption in Poland, focusing on insights from technically educated youth, early-career researchers, and academic professionals. Drawing on a mixed-methods approach, the study investigates public perceptions, motivations, and challenges associated with EV uptake in a country historically reliant on fossil fuels. Key drivers such as environmental considerations, government policies, and infrastructure development are evaluated alongside persistent obstacles, including high initial purchase costs, inadequate charging networks, range anxiety, and scepticism about battery performance. While the sample is not representative of the broader Polish population, it provides insights from a technically literate cohort likely to shape future technological and policy advancements. Our findings reveal that the adoption of EVs among this group is influenced by factors such as technological innovation and government policies, while barriers include high initial costs, limited charging infrastructure, and scepticism about perceived sustainability, battery life, and performance. The research also highlights the critical role of education and awareness in shaping attitudes toward EVs. This study, though limited by sample size and demographic focus, offers valuable contributions to understanding the early-stage adoption of EVs in Poland and serves as a foundation for future research targeting a more diverse population. The applied research model is scalable, providing a framework for broader studies that could include different age groups, geographical regions, and professional sectors. Full article

Integrating the electric motor with a multi-speed transmission is an effective way to improve the efficiency and performance of battery electric vehicles (BEVs). This paper innovatively proposes a design method for matching a single-motor and dual-speed dual-clutch transmission (2-Speed Wet DCT) powertrain system and constructs a variable speed efficiency model (VSEM) and constant speed efficiency model (CSEM) for the inverter, motor, and transmission. Research shows that the design parameters of the motor and transmission significantly affect the optimal powertrain system. This study uses an enhanced NSGA-II multi-objective genetic algorithm to optimize the driving performance of energy efficiency and powertrain cost under two different acceleration times (10 s and 12 s), with the key parameters of the motor and transmission as optimization variables and dynamic indicators as constraints, and compares VSEM and CSEM. The optimization results indicate that VSEM have better energy-saving effects than CSEM, with the energy consumption reduced by 3.7% and 3.3% under the two driving performances, respectively. The Pareto frontier further confirms that, for multi-speed transmission systems in electric vehicles, matching a high-power, high-torque motor with a smaller transmission ratio powertrain can achieve higher energy efficiency and thus longer driving range. Additionally, this study quantifies the correlation between energy efficiency and powertrain cost using grey relational analysis (GRA), with a result of 0.77431. Full article

In the automotive industry, battery electric vehicles (BEVs) represent the future of individual mobility. To establish a long-term market presence, innovative vehicle and powertrain concepts are essential, and therefore, identifying the most promising concepts is crucial to determine where to focus research and development further. Academia plays a significant role in this identification process; however, researchers often face restricted access to data from the industry, and identifying different technological approaches is often connected to significant costs. We present a comprehensive study of the Porsche Taycan Performance Battery Plus, which integrates two technological advancements: the first series-production implementation of a two-speed transmission in an electric vehicle allowing for high acceleration while reaching high top speeds and a 800 V battery system architecture providing more efficient charging capabilities. This study details vehicle dynamics, electric powertrain efficiencies, their impact on vehicle level, and the two technological advancements. This work aims to provide researchers access to vehicle dynamometer and real-world data from one of the most advanced and innovative battery electric sports cars. This allows for further analysis of cutting-edge technologies that have yet to reach the mass market. In addition to providing researchers with this study’s results, all data utilized in this study will be made available as open-access, enabling individual use of test data for parameter identification and the development of simulation models. Full article

Hydrogen Internal Combustion Engines (H₂ICEs) offer significant potential in reducing the CO₂ emissions of the heavy-duty transport sector in the pursuit of the European Green Deal targets. However, the challenges associated with hydrogen energy density require advanced technologies for fuel efficiency enhancement. Hybrid powertrains, equipped with innovative energy recovery systems, allow optimizing the engine working point while recovering otherwise wasted energy. In particular, Turbocompound (TCo) systems allow recovering the energy content in the exhaust gases, improving the overall efficiency of the powertrain. Optimizing both engine operation and TCo recovery presents a significant challenge, as it requires balancing the dynamic interaction between the engine’s combustion process and TCo (which increases backpressure). This paper presents a novel approach aimed at optimizing the performance of a hybrid hydrogen-fueled internal combustion engine by integrating a TCo system. The TCo allows extracting a 9 kW extra power peak with respect to the baseline configuration. The performance assessment of the optimized working point for series hybrid powertrains underscores the capability of the strategy to reduce hydrogen consumption up to 6.8%. Full article

Environmental and social governance targets, as well as the global transition to cleaner renewable energy sources, push for advancements in hydrogen-based solutions for energy generators due to their high energy per unit mass (energy density) and lightweight nature. Hydrogen’s energy density and lightweight nature allow it to provide an extended range of uses without adding significant weight, potentially revolutionizing many applications. Moreover, a variety of sources, including renewable energy, can produce hydrogen, making it a potentially more sustainable option for energy storage despite its main limitations in production and transportation costs. In this framework we are proposing an innovative energy generator that might merge the benefits of batteries and hydrogen. The energy generator is based on a worldwide patented solution introduced by MIEEG s.r.l. regarding the shape of the chambers. This innovative solution can be used to design a 100% H2-fed microturbine with a high power/weight/volume ratio that works as a range extender of battery packs for a comprehensive, high-efficiency hybrid powertrain. In fact, it runs at 100,000 rpm and is designed to deliver about 100 kW in about 15 L of volume and 15 kg of weight (alternator excluded). The system is highly complex due to high firing temperatures, long life requirements, corrosion protection, mechanical and vibrational stresses, sealing, couplings, bearings, and the realization of tiny blades. This paper analyzes the main design challenges to face in the development of such complex generators, focusing on the hot gas path components, which are the most critical part of gas turbines. The contribution of additive manufacturing techniques, the adoption of special materials, and coatings have been evaluated for system improvement. Full article

The Clean Propulsion Technologies (CPT) project, established in 2021, brought together 15 research partners and original equipment manufacturers. The goal was to create a common vision and sustainable business solutions so that the worldwide technological leadership of the Finnish powertrain industry is secured. With a EUR 15.5 M budget, CPT brought early-stage innovative concepts towards technology readiness level (TRL) 6. The project’s particular significance was its unique cross-coupling of marine and off-road sectors, which have similar emission reduction targets but which do not compete for similar customers. The project yielded 21 innovative solutions, from accelerated model-based design methodologies and progress in combustion and aftertreatment control to hybrid energy management solutions. These were encapsulated in four ground-breaking demonstrations, including a next-generation marine engine working in low-temperature, reactivity-controlled compression ignition (RCCI) mode and a hydrogen off-road engine. An advanced close-coupled selective catalyst reduction (SCR) system and a hybrid wheel-platform with digital hydraulics were also demonstrated. The University of Vaasa led the consortium and was responsible for coordinated model-based rapid prototyping. This report examines University of Vaasa’s achievements during the CPT in terms of 26 milestones, 13 deliverables, and 32 research papers. It focuses also on other aspects, including lessons learned from managing large-scale academic–industry research. Full article

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) is driving advancements in highway transportation by targeting energy efficiency, environmental sustainability, and cost reductions. This study investigates the fuel economy potential and cost implications of advanced powertrain technologies using comprehensive system simulations. Leveraging tools such as Autonomie and TechScape, developed by Argonne National Laboratory, this study evaluates multiple timeframes (2023–2050) and powertrain types, including conventional internal combustion engines, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs). Simulations conducted across standard regulatory driving cycles provide detailed insights into fuel economy improvements, cost trajectories, and total cost of ownership. The findings highlight key innovations in battery energy density, lightweighting, and powertrain optimization, demonstrating the growing viability of BEVs and their projected economic competitiveness with conventional vehicles by 2050. This work delivers actionable insights for policymakers and industry stakeholders, underscoring the transformative potential of vehicle electrification in achieving sustainable transportation goals. Full article

The imperative for electrification of road transport, driven by global climate targets, underscores the need for innovative powertrain systems in heavy-duty vehicles. When developing new electric drive modules, individual operational requirements need to be considered instead of generalized usage profiles, as heavy-duty vehicles experience significantly differing loads depending on their field of operation. Real driving data, representing the demands of different application scenarios, offers great potential for digital replication of driving conditions at different stages of simulation and physical validation. Application- and vehicle-specific longitudinal requirements during operation are particularly relevant for the dimensioning of powertrain components. Road gradient and mass estimation assist in the description of these operating conditions, allowing for detailed modeling of the real load conditions. An incorporation of real driving data instead of solely relying on standardized cycles has the potential of tailoring components to the target lead users and applications. While some operating conditions can be recorded by vehicle manufacturers, these are usually not accessible by third parties. In this paper, the authors present an innovative methodology of estimating vehicle parameters for the generation of representative driving profiles for implementation into a consecutive powertrain design process. The approach combines the measurement of real driving data with state estimation. The authors show that the presented methodology enables the generation of driving profiles with less than 25% deviation from the original data set. Full article

Reducing reliance on fossil fuels has driven the development of innovative technologies in recent years due to the increasing levels of greenhouse gases in the atmosphere. Since the automotive industry is one of the main contributors of high CO₂ emissions, the introduction of more sustainable solutions in this sector is fundamental. This paper presents a novel energy management system for fuel cell hybrid electric vehicles based on dynamic programming and adaptive neuro fuzzy inference system methodologies to optimize energy distribution between battery and fuel cell, therefore enhancing powertrain efficiency and reducing hydrogen consumption. Three different approaches have been considered for performance assessment through a simulation platform developed in MATLAB/Simulink 2023a. Further validation has been conducted via a rapid control prototyping device, showcasing significant improvements in hydrogen usage and operational efficiency across different drive cycles. Results manifest that the developed controllers successfully replicate the optimal control trajectory, providing a robust and computationally feasible solution for real-world applications. This research highlights the potential of combining advanced control strategies to meet performance and environmental demands of modern heavy-duty vehicles. Full article

To reduce the impact of the agricultural sector on the environment, human health and resource depletion, several steps should be taken to develop innovative powertrain systems. The agricultural sector must be involved in this innovation, since diesel-powered tractors are an important source in terms of pollution. In this context, fuel-cell systems have gained importance, making them one of the possible substitutes due to their characteristics featuring almost zero local emissions, low refueling time and high efficiency. However, to effectively assess the sustainability of a fuel-cell tractor, a cradle-to-grave life cycle assessment, comprising production, use phase and end of life, must be performed. This article presents a comparative analysis, according to different impact categories, of the life cycle impacts of a traditional diesel-powered tractor and a fuel-cell hybrid tractor, designed considering operative requirements and functional constraints. The study was conducted according to the LCA technique (defined by ISO 14040 and ISO 14044 standards), combining secondary data, mainly derived from studies and reports available in the literature, with the use of the Ecoinvent 3.0 database. The results are presented according to ten different impact categories defined by ReCiPe 2016 v 1.03 at the midpoint level. The findings obtained showed that the fuel-cell tractor allows for a relevant reduction in all the considered categories. The highest-impact reduction, more than 92%, was obtained in the human toxicity non-carcinogenic category, while the lowest reduction, around 4.55%, was observed for the fossil fuel scarcity category, mainly due to the adoption of gray hydrogen which is produced from fossil fuels. As for the climate change category, the fuel-cell tractor showed a reduction of more than 34% in the life cycle impact. Finally, the authors also considered the case of green hydrogen produced using solar energy. In this case, further reductions in the impact on climate change and fossil fuel resource depletion were obtained. However, for the other impact categories, the results were worse compared to using gray hydrogen. Full article

This comprehensive systematic review explores the multifaceted impacts of electric vehicle (EV) adoption across technological, environmental, organizational, and policy dimensions. Drawing from 88 peer-reviewed articles, the study addresses a critical gap in the existing literature, which often isolates the impact of EV adoption without considering holistic effects. Technological advancements include innovations in the battery technology and energy storage systems, enhancing EV performance and mitigating range anxiety. The environmental analysis reveals substantial reductions in greenhouse gas emissions, with lifecycle assessments showing significant reductions for EVs compared to internal combustion engine vehicles, particularly when charged with renewable energy sources. Key comparisons include lifecycle emissions between mid-size battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs), and global average lifecycle emissions by powertrain under various policy scenarios. The organizational implications are evident, as businesses adopt new models for fleet management and logistics, leveraging EVs for operational efficiency and sustainability. Policy analysis underscores the crucial role of government incentives, regulatory measures, and infrastructure investments in accelerating EV adoption. The review identifies future research areas such as efficient battery recycling methods, the potential impact of EVs on grid stability, and long-term economic implications. This study offers insights for stakeholders aiming to foster sustainable transportation and achieve global climate goals. Full article

The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles’ operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state. Full article

In response to the EU’s stringent zero-carbon emission standards for 2035 and global initiatives to phase out fossil-fuel-powered vehicles, there is an urgent need for innovative solutions in vehicle propulsion systems. While much of the current research focuses on electric passenger cars, commercial vehicles remain relatively underexplored despite their significant potential impact on carbon neutrality goals. This study presents an open-source Simulink model specifically tailored for the analysis of electric commercial trucks, concentrating on the 6.5-ton category. Developed to assess the influence of various power components and control strategies on driving range, the model incorporates three validated powertrain configurations and features such as regenerative braking and one-pedal drive. Simulations are conducted under two real-world driving scenarios in the city of Taipei in Taiwan to evaluate different configurations’ effects on energy consumption and efficiency. Results indicate that optimizing the vehicle configuration can reduce power consumption by 26.3% and extend driving range by an additional 25.1 km on a single battery charge. By making the model and its source code publicly available, this research not only fills a critical gap in specialized evaluation tools for electric commercial vehicles but also serves as a valuable resource for both industrial assessments and educational purposes in the field of vehicle electrification. Full article