Search

To minimize the negligence when charging electric vehicles, it is deemed important to have an internet of things (IoT) based monitoring system using a notification feature. The monitoring system of electric vehicle battery charging used a voltage divider and temperature sensor (DS18B20) installed on the Arduino Mega 2560 microcontroller with the addition of an ESP8266 Wi-Fi module for sending microcontroller data into the Blynk platform. A notification feature was added as the reminder that the battery has been overcharging or overheating. This study applied the Mamdani fuzzy logic method to determine the conditions when notifications must appear. The results of the application of the Mamdani fuzzy logic method were able to determine the conditions for push notifications to appear using the parameters as desired; by so doing, it is possible to create a battery monitoring system with accurate push notification feature to prevent the battery from being overcharged and overheated. [ABSTRACT FROM AUTHOR]

This study analyzes decarbonization costs for the Swedish heavy-duty road fleet under five scenarios, one taken from the EUCalc model as a reference scenario and four others driven by interviews: a high-speed transition with 100% battery electric vehicles (BEVs) across all distances; a high-speed transition with BEVs taking 100% of the market in local and regional distances and 40% in long distances, with the remaining 60% being fuel cell vehicles (FCVs) by 2050; a low-speed transition with BEVs market share increasing by 15% every five years, starting at 10% from 2025 for local and 2030 for regional and long distances; and a low-speed transition similar to the previous scenario, but with 60% of the electrified long-distance fleet to be FCVs. The system's expenses are then calculated through numerical modeling. The study links research on the costs of sustainability transition to a circular economy by analyzing the effect of charging range and temperature on battery degradation for BEVs and their impact on the batteries' valorization. In full electrification scenarios, despite lower operating expenses, the system incurs a higher total cost because of higher investment expenses. Charging–discharging pattern and temperature impact the remaining capacity, and therefore salvage value, of end-of-life batteries. • Develops a model evaluating the decarbonization costs of Swedish heavy-duty trucks. • Integrates cost savings from batteries' remaining capacity into the cost analysis. • Incorporates loading capacity and charging time loss into the cost analysis. • BEVs have a lower TCO in all scenarios and distances compared to diesel trucks. • A 70% EoL battery buyback rate leads to higher salvage value in BEVs. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have emerged as a promising solution to address environmental concerns, especially benefiting urban delivery and last-mile fleets due to their unique operational characteristics. Despite the potential advantages, the adoption of electric trucks (eTrucks) into delivery fleets has been slow, mainly due to the challenge posed by eTrucks' limited driving range. Consequently, a reliable method for predicting the eTrucks' energy consumption in fleet route planning is essential, and the accuracy of the velocity trajectory forecast forming the fundamental basis. This paper introduces a data-driven approach to predict the velocity and energy consumption of medium-duty (MD) eTrucks, considering various road features, payload, and traffic conditions. A gated recurrent unit (GRU) is trained using traffic-labeled characteristic features specific to each road segment within a delivery route. For every predefined route, the GRU generates the velocity profile by analyzing a sequence of traffic states predicted from the maximum entropy Markov model (MEMM). Corresponding eTruck energy consumption is estimated using an autonomie truck model. Real-world EV data are used to evaluate the proposed method, and the results demonstrate that the model effectively utilizes the information, achieving high accuracy in predicting both eTruck velocity and energy consumption. [ABSTRACT FROM AUTHOR]

As the country that emits the most carbon in the world, China needs significant and urgent changes in carbon emission control in the transportation sector in order to achieve the goals of reaching peak carbon emissions before 2030 and achieving carbon neutrality by 2060. Therefore, the promotion of new energy vehicles has become the key factor to achieve these two objectives. For the reason that the comprehensive transportation cost directly affects the end customer's choice of heavy truck models, this work compares the advantages, disadvantages, and economic feasibility of diesel, liquefied natural gas (LNG), electric, hydrogen, and methanol heavy trucks from a total life cycle cost and end-user perspective under various scenarios. The study results show that when the prices of diesel, LNG, electricity, and methanol fuels are at their highest, and the price of hydrogen is 35 CNY/kg, the total life cycle cost of the five types of heavy trucks from highest to lowest are hydrogen heavy trucks (HHT), methanol heavy trucks (MHT), diesel heavy trucks (DHT), electric heavy trucks (EHT), and LNG heavy trucks (LNGHT), ignoring the adverse effects of cold environments on car batteries. When the prices of diesel, LNG, electricity, and methanol fuels are at average or lowest levels, and the price of hydrogen is 30 CNY/kg or 25 CNY/kg, the life cycle cost of the five heavy trucks from highest to lowest are HHT, DHT, MHT, EHT, and LNGHT. When considering the impact of cold environments, even with lower electricity prices, EHT struggle to be economical when LNG prices are low. If the electricity price is above 1 CNY/kWh, regardless of the impact of cold environments, the economic viability of EHT is lower than that of HHT with a purchase cost of 500,000 CNY and a hydrogen price of 25 CNY/kg. Simultaneously, an exhaustive competitiveness analysis of heavy trucks powered by diverse energy sources highlights the specific categories of heavy trucks that ought to be prioritized for development during various periods and the challenges they confront. Finally, based on the analysis results and future development trends, the corresponding policy recommendations are proposed to facilitate high decarbonization in the transportation sector. [ABSTRACT FROM AUTHOR]

Copyright of Journal of South China University of Technology (Natural Science Edition) is the property of South China University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The hydrogen pressure typically increases to approximately 700-bar for storage in high-pressure tanks. Some industry applications use such a high-pressure hydrogen but some others need lower-pressure hydrogen where the pressure is reduced through pressure reduction valves. Some energy is lost during pressure reduction which would be significant in large-scale systems. A multi-level hydrogen storage can address this issue, where the hydrogen is stored at various pressures. This paper addresses an electricity-hydrogen nexus system integrated with multi-level hydrogen storage and solar PV sites. The designed system supplies electric and fuelcell vehicles at 3 different charging points including an electric vehicle charging station, fuelcell car refueling station, and fuelcell truck refueling station. The hydrogen is stored at 30, 350, and 700-bar pressure levels and each level feeds various users. The water electrolysis is employed to generate hydrogen at 30-bar pressure and 2 compressors increase the pressure to 350 and 700-bar. The cost function, defined as the daily energy cost, is optimized at $1045.65 per day. The water electrolyzer produces the most hydrogen during nighttime when electricity is inexpensive. Under normal operating conditions, the fuel cell is not utilized due to its low efficiency of about 60%. However, it serves as a backup resource in the event of a system outage, such as when the external grid fails, in hours 22 to 24. During this time, the fuel cell is activated and produces 154 kWh. • Multi-Level Hydrogen Storage. • Electricity-Hydrogen Nexus System Integration. • Optimized Hydrogen Production and Pressure Management. • Cost Optimization and Efficiency. • Backup Resource Utilization. [ABSTRACT FROM AUTHOR]

Climate change risks have triggered the international community to find efficient solutions to reduce greenhouse gas (GHG) emissions mainly produced by the energy, industrial, and transportation sectors. The problem can be significantly tackled by promoting electric vehicles (EVs) to be the dominant technology in the transportation sector. Accordingly, there is a pressing need to increase the scale of EV penetration, which requires simplifying the manufacturing process, increasing the training level of maintenance personnel, securing the necessary supply chains, and, importantly, developing the charging infrastructure. A new modular trend in EV manufacturing is being explored and tested by several large automotive companies, mainly in the USA, the European Union, and China. This modular manufacturing platform paves the way for standardised manufacturing and assembly of EVs when standard scalable units are used to build EVs at different power scales, ranging from small light-duty vehicles to large electric buses and trucks. In this context, modularising EV electric systems needs to be considered to prepare for the next EV generation. This paper reviews the main modular topologies presented in the literature in the context of EV systems. This paper summarises the most promising topologies in terms of modularised battery connections, propulsion systems focusing on inverters and rectifiers, modular cascaded EV machines, and modular charging systems. [ABSTRACT FROM AUTHOR]

As a core component of the powertrain system of Electric Logistics Vehicles (ELVs), the gearbox is crucial for ensuring the reliability and stability of ELV operations. Traditional fault diagnosis methods for gearboxes primarily rely on the analysis of vibration signals during operation. This paper presents research on diagnosing gear tooth wear faults in ELV powertrains using motor current signals. Firstly, an experimental test platform was constructed based on the structural principle of the powertrain of ELV models. Subsequently, a pure electric light truck powertrain gearbox with tooth wear was tested. Time–frequency domain analysis, amplitude analysis, ANOVA analysis, kurtosis analysis, and zero−crossing points analysis were used to analyze the U−phase current of the motor connected to the gearbox to study the characteristics of the phase current of the drive motor after tooth wear. The results indicate that while the time–frequency domain characteristics of the U−phase currents are not significantly altered by tooth wear faults, the amplitude, variance, and kurtosis of the current increase with the severity of the wear. Conversely, the number of zero−crossing points decreases. These findings provide valuable insights into new methodologies for diagnosing faults in ELV powertrain systems, potentially enhancing the efficiency and effectiveness of troubleshooting processes. [ABSTRACT FROM AUTHOR]

This paper investigates the competition between two charge point operators at the same site for future battery electric long-haul trucks. The charge point operators are located along one of the busiest highways in Sweden. The investigation is carried out using an agent-based model where trucks select charge point operators based on charging prices and the length of any queues, while charge point operators adjust their prices and number of chargers to improve their profitability. The study aims to predict conditions for trucks and charge point operators in a future public fast-charging market. Our findings indicate the potential for a well-functioning future public fast-charging market with small queuing problems, high utilisation, and reasonable prices for public fast charging. Assuming a price for electricity of EUR 0.08/kWh and a minimum profit margin of EUR 0.001/kWh for charge point operators, the findings indicate that the price level outside rush hours will be low, approximately EUR 0.1/kWh. The prices during rush hours will likely be much higher, but it is harder to predict the value due to uncertainties of how charge point operators will act in the future market. Still, from the model result, the price during rush hours is suggested to be just above EUR 0.5/kWh, with an average charging price of around EUR 0.15/kWh. It also seems likely that it is profitable for charge point operators to build enough chargers so that charging queues are short. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Several technological challenges delay the adoption of electrified powertrains in the heavy-duty transport sector. For fuel-cell hybrid electric trucks, key issues include slow cold start, reduced cooling power during high ambient temperatures, and uncertainties regarding durability. In addition, the engineers must handle the complexity of the system. In this article, a Matlab/Simulink library is introduced, which has been developed to aid engineers in the design and optimization of energy management systems and strategies of this complex system that consider mechanical, electrochemical, and thermal energy flows. The library is introduced through five example vehicle models, and through case studies that highlight the various kinds of analysis that can be performed using the provided models. All library code is open source, open for commercial use, and runs in Matlab/Simulink without any need for external libraries. [ABSTRACT FROM AUTHOR]

We propose an efficient truck trip chaining method to model freight fleet electrification using an agent-based simulation tool to simulate passenger and truck tours. The estimated truck trajectories are used to estimate vehicle energy consumption and emissions. The electricity demand estimate suggests that passenger vehicles have a significantly higher demand due to higher adoption and a larger fleet. Therefore, the truck fleet electrification efforts would not significantly affect the grid, but its adoption rates, along with passenger vehicle electrification, would cause issues. [ABSTRACT FROM AUTHOR]

Electric vehicles are attracting attention from the perspective of environmental protection. However, their short cruising range and insufficient charging infrastructure have hindered their widespread use. The home delivery industry is less affected by these characteristics, and demonstration experiments are already underway to replace delivery trucks with electric vehicles. Various studies have been conducted on electric vehicle routing problems. In most of these studies, delivery routes have been considered focusing on the travel distances of the electric vehicles. Recently, the problem of electricity supply has been changing due to the spread of solar power generation. Electricity market prices and carbon dioxide emissions during electricity generation now vary dramatically according to the time of day. The present paper considers the problem of minimizing costs and carbon dioxide emissions in electric vehicles used for deliveries, rather than the problem of the travel distance. The present paper proposes a mathematical model that extends the model of Schiffer and Walther〔1〕 to calculate charging costs and carbon dioxide emissions even in situations where electricity prices and carbon dioxide emissions depend on the time of day. It is possible to show appropriate routes by using the proposed mathematical model. In addition, the tradeoff among charging costs, carbon dioxide emissions, and travel distance is also discussed. As an application example of the model, the characteristics of the charging stations used and the reductions in charging costs and carbon dioxide emissions from electric vehicles in numerical experiments assuming real regions are also shown. [ABSTRACT FROM AUTHOR]

Battery-electric trucks offer a high battery capacity and good predictability, making them attractive for the implementation of bidirectional charging strategies. Nevertheless, most of the previous charging strategy studies focus on electric passenger cars. These charging strategies are usually formulated as separate use cases like tariff-optimized charging, arbitrage trading, peak shaving, and self-consumption optimization. By combining different use cases, their economic potential can be increased. In this paper, we introduce a model to optimize charging processes in depots for electric vehicles considering the combination of different use cases. This model is applied to a depot for battery-electric trucks. The savings obtained through optimized bidirectional charging highlight the enormous potential of this technology for the future, especially in the heavy-duty sector. [ABSTRACT FROM AUTHOR]

Electric vehicles are one of the most innovative and promising areas of the automotive industry. The efficiency of traction equipment is an important factor in the operation of an electric vehicle. In electric vehicles, the energy stored in the battery is converted into mechanical energy to drive the vehicle. The higher the efficiency of the battery, the less energy is lost in the conversion process, which improves the overall energy efficiency of the electric vehicle. Determining the performance characteristics of the traction battery of an electric vehicle plays an important role in the selection of the vehicle and its future operation. Using mathematical modelling, it is shown that battery capacity, charging rate, durability and efficiency are essential to ensure the comfortable and efficient operation of an electric vehicle throughout its lifetime. A mathematical model of an electric truck including a traction battery has been developed. It is shown that, with the help of the developed mathematical model, it is possible to calculate the load parameters of the battery in standardised driving cycles. The data verification is carried out by comparing the data obtained during standardised driving with the results of mathematical modelling. [ABSTRACT FROM AUTHOR]

Battery electric trucks (BETs) represent a well-suited option for decarbonizing road freight transport to achieve climate targets in the European Union. However, lower ranges than the daily distance of up to 700 km make charging stops mandatory. This paper presents an online algorithm for optimal dynamic charging strategies for long-haul BET based on a dynamic programming approach. In several case studies, we investigate the advantages optimal strategies can bring compared to driver decisions. We further show which charging infrastructure characteristics in terms of charging power, density, and charging station availability should be achieved for BETs in long-haul applications to keep the additional time required for charging stops low. In doing so, we consider the dynamic handling of occupied charging stations for the first time in the context of BET. Our findings show that, compared to driver decisions, optimal charging strategies can reduce the time loss by half compared to diesel trucks. To keep the time loss compared to a diesel truck below 30 min a day, a BET with a 500 kWh battery would need a charging point every 50 km on average, a distributed charging power between 700 and 1500 kW, and an average charger availability above 75%. The presented method and the case studies' results' plausibility are interpreted within a comprehensive sensitivity analysis and subsequently discussed in detail. Finally, we transformed our findings into concrete recommendations for action for the efficient rollout of BETs in long-haul applications. [ABSTRACT FROM AUTHOR]

With the continual expansion of urban road networks and global commitments to net zero, electric vehicles (EVs) have been considered to be the most viable solution to decarbonize the transportation sector. In recent years, the electric road system (ERS) has been introduced and piloted in a few countries and regions to decarbonize heavy-duty vehicles. However, little research has been carried out on its reliability. This paper fills the gap and investigates the reliability of electric truck power supply systems for electric road (ETPSS–ER), which considers both the power system and truck traffic networks. First, a brief introduction of electric roads illustrates the working principle of EV charging on roads. Then, an optimized electric truck (ET) travel pattern model is built, based on which the corresponding ET charging load demand, including both static charging and dynamic charging, is conducted. Then, based on the new ET travel pattern model, a daily travel-pattern-driven Monte Carlo simulation-based reliability assessment method for ETPSS–ER system is presented. Case studies based on the IEEE RBTS system shows that ETs driving on ERS systems can meet the daily travel demands. The case studies also examine the impacts of increasing number of ETs, extra wind power, and battery energy storage systems (BESS) on the reliability of ERS power systems. [ABSTRACT FROM AUTHOR]

Trending electric vehicles with different battery technologies need universally compatible and fast chargers. Present semiconductor technology is not suitable for designing high-power-rating converters. The increasing demand for high-capacity electric vehicle chargers requires efficient and optimum advanced material technology. This research presents next-generation material-based smart ultra-fast electric vehicle charging infrastructure for upcoming high-capacity EV batteries. The designed level 4 charger will be helpful for charging future heavy-duty electric vehicles with battery voltages of up to 2000 V. The designed infrastructure will be helpful for charging both EVs and heavy-duty electric trucks with a wide range of power levels. Wireless sensor-based smart systems monitor and control the overall charging infrastructure. The detailed design analysis of the proposed charger using the Simscape physical modeling tool is discussed using mathematical equations. [ABSTRACT FROM AUTHOR]

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]

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 majority of freight in Germany is carried out by trucks, resulting in emitting approximately 9% of Germany's carbon dioxide equivalent emissions. In particular, long-distance truck journeys contribute significantly to these emissions. This paper aims to explore the conditions and impacts of introducing E-Trucks in Germany by utilizing a microscopic traffic simulation approach. Therefore, five different electrification levels of the long-distance truck traffic are evaluated. The demand-oriented charging network dimensioning aims for a realistic and implementable design and is based on an average charging power of 720 k W. Additionaly, it considers the necessary infrastructure requirements at service and rest areas next to the motorway. The results of this research provide valuable insights in terms of usage, requirements and demand. For an electrification level of 1%, 177 chargers at 173 charging sites must be implemented, while 1296 chargers and 457 charging sites must be built for an electrification level of 20%. The increase in the electrification level leads to more efficient occupancy of the charging facilities; i.e., an increase from 1% to 5% improves the average occupation time ratio per charger by approximately 130%. Of the total energy consumed, 65% is recharged en-route at public chargers. Between Monday and Thursday, each 1% electrification level increase requires 2.68 G W   h more energy for the public recharging network. [ABSTRACT FROM AUTHOR]

This paper investigates the charging needs and charger utilisation of a system of battery electric trucks and their public fast chargers, along the highway between the Swedish cities of Helsingborg and Stockholm, in a possible future scenario in which all trucks are battery electric. The system is investigated via an agent-based model which simulates a typical day with current levels of truck traffic on the road. The traffic flow is based on hourly truck flow data during a day and the annual flow of trucks. The findings indicate major potential for a well-functioning system of public chargers for trucks, with high utilisation, few queuing problems at charging stations, cheap public fast charging and a robust response to queues caused by peaks or increases in the traffic flow. The number of 900 kW chargers along the road needed to achieve this has been estimated at 140, and the utilisation factor for the chargers is predicted to be 30%. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the work is to determine whether and how the local government authorities of the largest cities in Poland apply reliefs and exemptions in the tax on means of transport to support owners of hybrid and electric trucks. In addition, an answer was sought to the question whether the amount of the aforementioned preferences was correlated with the dynamics of the number of vehicles powered in whole or in part by electricity in the analyzed period. Methodology: The study covered all 63 cities in Poland with poviat rights. The resolutions adopted by the local government authorities of these centers in 2018-2020 regarding the rates of tax on means of transport were reviewed. Based on the texts of legal acts, the criteria used for granting tax preferences were defined, the amount of reliefs was calculated, and the statistical tool in the form of the Pearson correlation coefficient was used to check whether there is a relationship between the scale of tax benefits and the growth rate of the number of hybrid and electric vehicles. Findings: It was found that only half of the municipalities used reduced tax rates in the analyzed period, while different requirements regarding the level of exhaust gas emissions were adopted in different local government units, so that owners of hybrid and electric trucks in individual cities could usually benefit from the reduction on an equal footing with owners of similar vehicles with lower but also different emission standards from Euro 1 to Euro 6. Practical implications: The results of the research can be used by local governments. They show, among other things, that the mere reduction of tax rates is insufficient for the promotion of environmentally friendly means of transport and that these activities should also be supported by other solutions. Originality/value: In the literature, the subject of differentiation of tax rates on means of transport to stimulate the increase in the number of rolling stock powered by electricity has not been generally taken up so far or has been the subject of research very rarely. [ABSTRACT FROM AUTHOR]

Because of the rising demand for CO2 emission limits and the high cost of fuel, the electrification of heavy-duty vehicles has become a hot topic. Manufacturers have tried a variety of designs to entice customers, but the outcomes vary depending on the application and availability of recharging. Without affecting vehicle range, plug-in hybrids provide a potential for the automobile industry to reach its CO2 reduction objectives. However, the actual CO2 emission reductions will largely rely on the energy source, user behavior, and vehicle design. This research compares a series plug-in hybrid medium-duty truck against two baselines: nonhybrid and pure electric commercial trucks. As well as evaluating and contrasting the different tools to quantify CO2 emissions, this manuscript offers fresh information on how to simulate various powertrain components used in electrified vehicles. According to the findings, plug-in hybrids with batteries larger than 50 kWh can reduce emissions by 30%, while still meeting the 2030 well-to-wheel CO2 regulations. The recommended battery size for plug-in hybrid is 100 kWh, and for electric vehicles it is 320 kWh. The range of a plug-in hybrid is 18% longer than that of nonhybrid, 6% longer than that of a full hybrid, and 76% longer than that of a pure electric powertrain with a fully charged battery. [ABSTRACT FROM AUTHOR]

This paper investigates the economic consequences of a haulage company replacing its line-haul diesel trucks with battery-electric ones. It also examines how large truck batteries should be, whether the haulage companies should use public fast chargers to complement their own, and whether public fast chargers have the potential to be profitable. The potential extra cost of losing payload capacity is estimated and there is an investigation of whether a charge-point operator should meet the peak demand for charging. The case under analysis is designed to represent a typical line-haul service between terminals in a major logistics system, with the finding that, in this case, a transition to battery-electric trucks seems cost effective for the company. Moreover, it is advisable for the company to use public fast chargers and these will likely become profitable given that the utilisation factor of the investigated public fast chargers may realistically exceed 20%. [ABSTRACT FROM AUTHOR]

[Display omitted] • The proposed model combines renewable-based fuel cycle and vehicle cycle. • Five heavy-duty vehicle decarbonization pathways are compared. • The impacts of gross vehicle weight and vehicle range are explored. • Battery electric trucks offer a 7 % lower ton-km cost than diesel trucks. • Fuel cell electric trucks become more cost-effective at ranges over 1100 km. Decarbonizing heavy-duty vehicles is becoming increasingly important, yet multiple renewable-based decarbonization pathways have not been compared systematically. To fill this gap, this study develops a techno-economic and environmental model that integrates the fuel cycle and vehicle cycle to assess these pathways for China. The model includes two energy storage technologies: batteries and hydrogen, three energy transmission options, and two vehicle types: fuel cell electric vehicles and battery electric vehicles. Five distinct low-carbon pathways are evaluated on a ton-kilometer basis, including cost, greenhouse gas emissions, and abatement cost relative to conventional diesel trucks. Results indicate that the most cost-effective battery electric vehicle pathway offers a 7 % lower ton-km cost than diesel trucks for a 49-ton gross vehicle weight. Battery electric vehicle charging combined with hydrogen for power generation is more cost-effective than direct use of hydrogen in fuel cell electric vehicles. All studied pathways can achieve over 80 % emission reduction compared to diesel trucks, with fuel cell electric vehicle pathways having the highest abatement costs of 103–117 USD/tonCO 2. Analysis of the impact of gross vehicle weight and vehicle range indicates that battery electric vehicle pathways outperform fuel cell electric vehicle pathways across most dimensions. Costs of battery electric vehicle pathways do increase sharply for vehicle ranges beyond about 700 km, and fuel cell electric vehicles become more cost-effective relative to battery electric vehicles for ranges above approximately 1100 km, although all pathways are much more costly than diesel trucks at long ranges. The sensitivity analysis highlights the importance of powertrain efficiency and cost projections show that fuel cell electric heavy-duty vehicles can achieve cost-parity before 2030. These results highlight the desirability of promoting the adoption of heavier battery electric vehicles and providing more targeted subsidies for long-range fuel cell electric vehicles. [ABSTRACT FROM AUTHOR]

Electrifying road-based long-haul transportation is an intricate task. Given the current state of battery technology, either the driving ranges of electric commercial vehicles (ECVs) are too short or high-capacity batteries are costly and so heavy that payloads are limited. An old, yet recently revitalized, charging infrastructure currently evaluated on multiple test tracks around the globe alternatively suggests charging of electric trucks while driving. Analogously to trams, trolley buses, or trains, ECVs are powered by an electric motor connected to overhead wires via a movable contact arm and supported by a battery or an extra conventional drive, which steps in on non-electrified road segments. This paper is dedicated to the routing of a single ECV executing full-truckload point-to-point deliveries along a highway main line where charge-while-drive infrastructure is fixedly installed along some but not all parts of the road. We formulate the resulting optimization problem, investigate computational complexity, and provide suitable solution procedures based on decomposition. Once all this is available, we explore the induction effect of charge-while-drive technology, i.e., the amount of charging detours required to gather enough energy for the next job. Our results show that the induction effect can be considerable and may lead to substantial extra traffic compared to conventional charge-while-park technology. [ABSTRACT FROM AUTHOR]

One possible step for reducing humans' use of fossil fuel due to transport tasks is to replace diesel trucks with battery electric ones. This paper introduces the energy distribution diagram, which makes it easy to visualise the trucks' daily energy consumption over their full service life. The energy distribution is used to investigate which driving patterns are suitable for cost-effective battery electric trucks when compared to commercial diesel trucks. It is shown that the battery capacity that results in the lowest cost per kilowatt-hour propulsion energy depends on the driving pattern, and an algorithm for selecting the most cost-effective capacity is presented. In many instances, it was found that battery electric trucks competed favourably with diesel trucks, especially when the trucks had low variations in daily energy consumption. It is beneficial to determine the circumstances under which they may be cheaper, as this will facilitate the transition to battery electric trucks in segments with a reduced overall cost of ownership. [ABSTRACT FROM AUTHOR]