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Electric vehicles are the most innovative and promising area of the automotive industry. The efficiency of a traction battery is an important factor in the performance of an electric vehicle. This paper presents a mathematical model of an electric truck, including modules for the traction battery to determine the depth of battery discharge during the operation of the electric truck, a traction electric system for the electric truck and a system for calculating traction forces on the shaft in electric motors. As a result of the modelling, the charging and discharging currents of an accumulator battery in a real cycle of movement in peak and nominal modes of operation in electric motors and at different voltages of the accumulator battery are determined. A functional scheme of a generalized model of the electric vehicle traction electrical equipment system is developed. An experimental battery charge degree, torques of asynchronous electric motors, temperature of electric motors and inverters, battery voltage and the speed of electric motors have been measured and analysed. The developed complex mathematical model of an electric vehicle including a traction battery, two inverters and two asynchronous electric motors integrated into an electric portal bridge allowed us to obtain and study the load parameters of the battery in real driving cycles. Data were verified by comparing simulation results with the data obtained during driving. [ABSTRACT FROM AUTHOR]

In addition to passenger vehicles, battery-electric trucks and buses could offer substantial flexibility to the energy system. Using a Bass diffusion model, we extrapolated the unidirectional charging needs and availability of trucks in five of eleven typical applications, as well as city buses, for Germany until 2040. Combined, these heavy-duty vehicles could provide up to 23 GW of down-regulating flexibility potential (i.e., in case of excess power supply) in 2040. The resulting revenues could contribute to reducing electricity costs for depot operators. These results illustrate the need to provide easy and automated market access to heavy-duty vehicle fleets. [ABSTRACT FROM AUTHOR]

This study investigates the potential and economics of hydrogen as a clean energy to satisfy the energy demand and reduce emissions. Heavy-duty vehicles and hydraulic fracking processes, which consume significant amounts of diesel are introduced as pilot markets for hydrogen. The technical, economic, and environmental aspects of both markets are provided. Then, a case study of the Permian Basin is rendered to show the effects of hydrogen in the region. In this study, the HDSAM model is used to obtain the cost of hydrogen. A function to predict the hydrogen demand for hydraulic fracking is provided based on real data. The results obtained in this study are as follows. First, the results for heavy-duty vehicles show that hydrogen demand is equal to 148 (tonnes/day), and hydrogen cost is 7.58 ($/kg). The refueling station is the major contributor to the hydrogen cost. Among refueling station components, compressor and storage induce significant costs. Liquid hydrogen is cheaper than gas hydrogen. Switching costs from diesel trucks to hydrogen trucks is equal to 0.65 ($/miles). If the payload and dwell time costs are considered, hydrogen trucks can even be cheaper than EV trucks. Second, the results for hydraulic fracking show that hydrogen demand is equal to 334 (tonnes/day) considering 1430 wells in the Permian Basin. The hydrogen cost is 4.22 ($/kg). If hydrogen is used instead of diesel in fracking, 3.41 × 10 6 kg C O 2 -eq as well as 4.10 × 10 7 kg of N O x can be saved from emissions. The hydrogen cost is equal to or even less than the diesel cost to generate 1 horsepower-hour for hydraulic fracking. This work can be expanded by investigating ammonia. Its features can be compared with hydrogen in terms of stability for long-term storage, transmission, and the globally established infrastructure. In addition, the tax credits of 45Q can be compared with 45 V and its effects can be analyzed. • Two markets with high potential demands for hydrogen are studied in detail. • The technical, economic, and environmental aspects of the hydrogen are provided. • The total demands and costs of hydrogen for the pilot markets are determined. • A function to predict hydrogen demand for fracking is rendered based on real data. • Hydrogen is compared with diesel to help stakeholders make optimal decisions. [ABSTRACT FROM AUTHOR]

The road freight sector faces significant challenges in decarbonisation, driven by high energy demand and limited availability of low-emission fuels and commercialised zero-emission vehicles. This study investigates intangible costs associated with advanced electric and hydrogen-powered trucks, including recharging/refuelling time, cargo capacity limitations, and buyer reluctance towards emerging technologies. Utilising a comprehensive whole-systems modelling approach considering low- and zero-emission fuels, inter-sectoral dynamics, and the carbon budget, we explore cost-optimal decarbonisation pathways for heavy, medium, and light trucks. Scenario and sensitivity analyses reveal the following insights: (1) Electric trucks dominate the market under mitigation pathways across all weight categories. However, the inclusion of intangible costs triggers a shift, leading to the emergence of hydrogen fuel cell vehicles for heavy trucks, while battery electric vehicles are preferred for medium and small trucks. (2) Prioritising heavy truck decarbonisation and taking early action are crucial to avoid carbon lock-in effects. (3) Considering limited decarbonisation options, where electric and hydrogen-fuelled trucks are pivotal, this research highlights the significance of policy instruments targeting operational expenditures over conventional purchase price incentives. Such policies offer dual benefits by supporting truck owners and directing incentives more precisely towards achieving measurable emission reductions. [ABSTRACT FROM AUTHOR]

The deployment of new energy trucks is a crucial national strategy in China to achieve deep decarbonization in road transport. Although fuel cell trucks and electric tucks are regarded as alternatives to conventional fuel trucks due to the advantage of zero usage emissions, their applicability for each truck type has not been determined. By developing a total cost of ownership analysis, this study dynamically determines the most economical alternative fuel type for each truck type and identifies when the large-scale deployment of new energy trucks is economically achievable. Then, by conducting a life cycle analysis with a localized database, this study quantitively evaluates the green gashouse emission intensities and their possible changes of different types of trucks. Finally, the emission reduction potential in the truck fleet by applying fuel cell and alternative fuel during 2020–2050 is comprehensively evaluated. The main results suggest that electric trucks are economically suitable for mini and light-duty trucks by 2031 and 2026, while fuel cell trucks suit medium-duty and heavy-duty trucks by 2027 and 2032. The application of alternative fuels in the truck fleet could achieve 28% carbon emissions in 2030 and up to 80% in 2050. • Analyzes TCO and GHG for Chinese trucks, identifies new energy types for different trucks. • Electric trucks viable for mini and light-duty by 2031 and 2026, fuel cell for medium and heavy-duty by 2027 and 2032. • Electric trucks emit 11.9–61.4% less GHG than diesel in 2020, expected to exceed 90% by 2050. • Hydrogen costs to decrease, making fuel cell trucks economically viable for heavy-duty transportation. • Study recommends policy measures for new energy trucks, including incentives, infrastructure, and regulations. [ABSTRACT FROM AUTHOR]

With growing demands to save greenhouse gases, the rapid market introduction of battery-electric trucks (BETs) will become increasingly important, with truck manufacturers announcing various models entering the market in the near future. Soon, truck operators will be faced with deciding which battery capacity and cell chemistry to choose in their next purchase. In this study, we evaluate the choice of battery capacity, regarding feasibility and cost-effectiveness, for trucks using NMC and LFP cell chemistry. Our results show that higher energy density allows larger NMC batteries to be installed, resulting in the ability to transport higher payloads at low charging powers. The LFP chemistry has to rely on higher charging powers of up to 700 kW to transport the same payloads. When asked to choose a battery capacity for the individual use case, the smallest battery size should always be selected when only charging powers up to 300 kW are available. However, the reduction in publicly charged energy can lead to cost advantages of larger battery capacities at higher charging powers. When deciding between the two cell chemistries, the LFP chemistry shows advantages in most cases. Only at high payloads and low charging powers the NMC chemistry shows cost advantages. [ABSTRACT FROM AUTHOR]

The heavy-duty vehicle sector is responsible for over 25% of the greenhouse gas emissions generated by road transport in the EU. In order to achieve their ambitious objectives stated in the" Fit for 55" Package, the European Institutionshave to provide the legal framework, that will compel the member states to assure the infrastructure to support the transition towards more sustainable modes of transport, and to put the Union on track for the full decarbonization of the transport sector by 2050. Thus, the new Alternative Fuels Infrastructure Regulation (AFIR) - part of "Fit for 55" Package, has to ensure there is sufficient public charging infrastructure to follow the deployment of zero emission cars and semi-trailer trucks. Accordingly, the top ranked European semi-trailer truck makershave to align their industrial plans and business activity to fully transition to zero-emission semi-trailer truck sales. The purpose of this analysis is to evaluate the possibility of a heavy-duty electric semi-trailer truckto carry out a trip on a frequent commercial route between Romania and Germany. The scientific paper is based on an analysis in the form of a case study generated on the basis of a theoretical requirement. The results will show to what extent electric vehicles and infrastructure are ready for this type of transport. After results examination, we found that our findings overlap with the literature and that there is still much room for improvement in this area. Major changes are needed, namely additional investments in infrastructure and subsequent detailed analyses of the opportunity to develop the use of electric vehicles.. [ABSTRACT FROM AUTHOR]

The successful introduction of battery electric trucks heavily depends on public charging infrastructure. But even as the first trucks capable of long-haul transportation are being built, no coherent fast-charging networks are yet available. This paper presents a methodology for assessing fast charging networks for electric trucks in Germany from the literature. It aims to establish a quantitative understanding of the networks' performance and robustness to deviations from idealized system parameters and identify crucial charging sites from a transportation planning perspective. Additionally, the study explores the quantification of adaptation effects displayed by agents in response to charging site outages. To achieve these objectives, a comprehensive methodology incorporating infrastructure, vehicle and operational strategy modeling, simulation, and subsequent evaluation is presented. Factors such as charging station locations, C-rates, mandatory rest periods, and vehicle parameters are taken into account, along with the distribution of traffic according to publicly available data. The study aims to offer a comprehensive understanding of charging networks' performance and resilience. This will be applied in a case study on two proposed networks and newly created derivatives. The proposed network offers over 99% coverage for long-haul transport but leads to a time loss of approximately 7% under reference conditions. This study advances the understanding of the performance and resilience of proposed charging networks, providing a solid foundation for the design and implementation of robust and efficient charging infrastructure for electric trucks. [ABSTRACT FROM AUTHOR]

Currently, the focus of integrated energy system scheduling research is the multi-objective's optimized operational strategies that take into account the economic benefits, carbon emissions, and new energy consumption rates of such systems. The integration of electric trucks with battery charging and swapping capabilities, along with their corresponding battery swapping stations, into an integrated energy system can not only optimize system operation, but also reduce investment costs associated with building energy storage equipment. This study first constructs an operational model for the electric trucks, as well as an electric truck battery swapping station, of the flexible charging and discharging; then, an optimized scheduling model of an integrated energy system is proposed, including an electric truck battery swapping station and using stepped carbon trading. On the basis of meeting the charging and battery swapping needs of electric trucks and coordinating the system's electrical, thermal and cooling energies, the goal of the optimized scheduling model is to reduce the system's carbon emissions, improve its economics, and optimize its ability to absorb new energy. Finally, a simulation model of the integrated energy system including an electric truck battery swapping station is built on the MATLAB platform, and commercial software package CPLEX is used to solve the model. In the calculation example, compared to the integrated energy system of disorderly charging and battery swapping of electric trucks and electric truck battery swapping stations, the proposed optimized model of the integrated energy system with the flexible charging and discharging of electric trucks and electric truck battery swapping stations reduces the operating costs by CNY 819, reduces carbon emissions by 414 kg, improves the utilization rate of wind and solar power by 0.3%, and fully utilizes wind and photovoltaic power. Therefore, the rational dispatching of the electric trucks and their battery swapping stations with flexible charging and discharging mentioned in this article can effectively optimize system operations. [ABSTRACT FROM AUTHOR]

Polymer electrolyte membrane fuel cells (PEMFCs) are employed in trucks and large commercial vehicles utilizing hydrogen as fuel due to their rapid start-up characteristics and responsiveness. However, addressing the requirement for high power output in the low-current section presents a challenge. To solve this issue, a multi-stack can be applied using two stacks. Furthermore, thermal management, which significantly affects the performance of the stacks, is essential. Therefore, in this study, a hydrogen electric truck system model was developed based on a Hyundai Xcient hydrogen electric truck model using MATLAB/SimscapeTM 2022b. In addition, the system's performance and thermal characteristics were evaluated and analyzed under different road environments and wind conditions while driving in Korea. [ABSTRACT FROM AUTHOR]

Due to the rapid increase in the use of electric vehicles and instability in energy supply, the application of vehicle-to-grid (V2G) technology has gained attention in the freight transportation sector. V2G has the potential to increase the efficiency of power grid and make additional profits by utilizing surplus power from electric vehicle batteries. This paper proposes an optimization model for electric trucks (ETs) to provide operational decision-making support for the freight transportation sector. The objective of the model is to minimize the total net cost, which includes charging cost, discharging reward, and time penalties, while considering changes in ET charging cost and the system marginal price. Furthermore, we conduct sensitivity analysis in the vehicle routing problem with soft time windows using ETs in the V2G system. [ABSTRACT FROM AUTHOR]

There is developed mathematical model of transmission for rear-wheel electric cargo truck taking into account motion of driving shaft including Cardan joints. Model focuses on consideration of the rotary, motion in the shaft in difficult working conditions. There are analyzed dynamic conditions of shaft operating on the flat and rough roads in the both states: dynamic and static as well. Mathematical model is realized by the fourthorder Runge-Kutta method. Computer simulation results are demonstrated and analyzed in the figures. [ABSTRACT FROM AUTHOR]

Similar to many complex systems, the operation process of electric balanced forklifts has characteristics such as time-varying model parameters and nonlinearity. Establishing an accurate mathematical model becomes challenging, making it difficult to apply model-based control methods in engineering practice. Aiming at the longitudinal control system of electric forklifts containing external disturbances, this paper proposes an improved full-format dynamic linearization model-free adaptive PID control (iFFDL-MFA-PID) method. Firstly, the full-format dynamic linearization (FFDL) method is employed to transform the operating system of the electric balanced forklift into a virtual equivalent linear data model. Secondly, the nonlinear residual term and pseudo-gradient (PG) of the data model are estimated using the difference estimation algorithm and the optimal criterion function, respectively. Furthermore, in order to enhance the robustness of the system, the idea of intelligent PID (iPID) is introduced and the principle of equivalent feedback is utilized to derive the iFFDL-MFA-PID control scheme. The design process of this scheme only requires the use of the input and output data of the system, without relying on the mathematical model of the system. Finally, the iFFDL-MFA-PID method proposed in this paper is simulated and tested with the EFG-BC/320 counterbalanced forklift equipped in the Special Equipment Testing Center and compared with the model-free adaptive control method (FFDL-MFAC) and the PID control method. Simulation results show that the speed-tracking error of the electric forklift truck under the action of the iFFDL-MFA-PID algorithm is maintained within ±0.132 m/s throughout the process, achieving higher tracking accuracy and better robustness compared to the MFAC and PID methods. [ABSTRACT FROM AUTHOR]

Electric drones as an autonomous mode of transport are scaling up to transform last-mile goods delivery, raising an urgent need for assessing impacts of drone transport from a systems perspective. In this paper, we conduct systems analyses to assess the environmental, economic, and delivery time impact of large drones for delivery scenarios to pick-up centers between mid-size cities predominantly in rural areas, and deliveries within city limits compared with electric and diesel trucks. Results show that large drones have lower emissions than diesel trucks for deliveries in rural areas and that drones don't compete with electric trucks, mainly due to the high energy demand required for take-off and landing for each delivery. Furthermore, we show that electric drones are an economically more cost-effective option than road-bound transport modes such as diesel and electric trucks due to the high degree of automation, and also provide the fastest delivery times. Our analysis provides unique insights that drones can address rapid electrification and emergency applications due to low costs, high flexibility, and fast operations. However, for regulators and practitioners to realize it as an emission-friendly option it is necessary to determine the optimal size of drones, particularly for use cases in urban areas, avoid very low landings for deliveries, and have home deliveries instead of pick-up points. [ABSTRACT FROM AUTHOR]

In order to understand the driving characteristics of electric heavy-duty trucks in practical application scenarios and promote their usage to replace diesel trucks, this study analyzed the actual usage of electric and diesel heavy-duty trucks in a steel factory based on vehicle-monitoring data and remote online monitoring data and estimated the emission reduction potential of the application of electric trucks by using a mileage-based method and the greenhouse gas emission model. The results showed that the electric heavy-duty trucks in the steel factory mostly operated for over 14 h, with a vehicle kilometers traveled (VKT) of 50–300 km each day, which could meet most of the demands of the transportation of the steel industry. The average daily energy consumption for most trucks falls within the range of 210–230 kWh/100 km, with higher consumption in winter than in summer, which can save approximately 18–26% in operating costs compared with diesel trucks. It is estimated that the usage of these electric heavy-duty trucks can achieve an annual reduction of 115.8 tons of NOx emissions, 0.7 tons of PM emissions, and 18,000 tons of CO2 emissions. To further promote the application of electric heavy-duty trucks in China, several policy suggestions, such as introducing priority road-right policies, promoting vehicle and battery leasing markets, and exempting zero-emission vehicles during heavy pollution days, were proposed. [ABSTRACT FROM AUTHOR]

Mitigating CO2 emissions from long-haul commercial trucking is a major challenge that must be addressed to achieve substantial reductions in greenhouse gas (GHG) emissions from the transportation sector. Extensive recent research and development programs have shown how significant near-term reductions in GHGs from commercial vehicles can be achieved by combining technological advances. This paper reviews progress in technology for engine efficiency improvements, vehicle resistance and drag reductions, and the introduction of hybrid electric powertrains in long-haul trucks. The results of vehicle demonstration projects by major vehicle manufacturers have shown peak brake thermal efficiency of 55% in heavy-duty diesel engines and have demonstrated freight efficiency improvements of 150% relative to a 2009 baseline in North America. These improvements have been achieved by combining multiple incremental improvements in both engine and vehicle technologies. Powertrain electrification through hybridization has been shown to offer some potential reductions in fuel consumption. These potential benefits depend on the vehicle use, the details of the powertrain design, and the duty cycle. To date, most papers have focused on standard drive cycles, leaving a research gap in how hybrid electric powertrains would be designed to minimize fuel consumption over real-world drive cycles, which are essential for a reliable powertrain design. The results of this paper suggest that there is no "one-size-fits-all" solution to reduce the GHGs in long-haul trucking, and a combination of technologies is required to provide an optimum solution for each application. [ABSTRACT FROM AUTHOR]

The development of battery electric (BE) heavy-duty trucks (HDTs) is highly limited to the short cycling life of batteries. In this paper, we propose a battery aging-conscious control strategy for extended battery life by optimizing the speed trajectory of BE HDT. A state-space model is constructed by connecting the vehicle dynamics and battery state of charge, and a mechanism-based aging model of battery is then introduced to formulate the optimization problem for minimal battery aging and energy consumption. The optimization problem is solved within a model predictive control framework for the real-time speed control of the vehicle A non-cooperative platooning controller is further developed for the vehicle in adaptation to the traffic, where the intervehicular distance is controlled for reducing the air drag coefficient so that both the energy consumption and battery aging are improved. Simulation results show that for the single-vehicle controller, the battery degradation and energy consumption are, respectively, reduced by up to 25.7% and 3.2% compared with the cruise control strategy. Based on the non-cooperative controller, the HDT is able to follow preceding vehicles with different parameters with battery aging and energy consumption further, respectively, reduced by 2%–5% and 9%–10% compared with those of the single-vehicle controller. [ABSTRACT FROM AUTHOR]

Heavy-duty vehicles are a major contributor to CO2 emissions in the transportation sector, and it is necessary to develop clean and green technologies to replace diesel trucks. Electric trucks have not reached a breakthrough in the German market. In addition to technology development, customer acceptance of new technologies is a critical factor in the success of sustainable transportation policies. This study aims to fill this knowledge gap by investigating the perceptions regarding electric trucks and providing insights into the acceptance of these technologies. Data and arguments on the expected risks and benefits of heavy-duty electric trucks, with a special focus on the battery swapping solution, were collected through a survey and expert interviews in the German commercial transport sector. The authors collected a sample of 146 qualitative responses and 61 individual statements on the expected risks and benefits of electric trucks and battery swapping. While the responses to the classified questions are overwhelmingly positive, the individual statements show that there are still many open questions. [ABSTRACT FROM AUTHOR]