Total Cost of Ownership and Its Potential Consequences for the Development of the Hydrogen Fuel Cell Powered Vehicle Market in Poland

Fuel cell-based electric vehicles technologies and challenges

Electric vehicles (EVs) are becoming popular and are gaining more focus and awareness due to several factors, namely the decreasing prices and higher environmental awareness. EVs are classified into several categories in terms of energy production and storage. The standard EV technologies that have been developed and tested and are commercially available include the fuel cell electric vehicles (FCEVs), the battery-electric vehicles, the plug-in hybrid electric vehicles, the hybrid electric vehicles, and the flexible fuel vehicles. Yet, the FCEVs show relatively small superiority over the other technologies from autonomy and refueling. The paper presents a review of EVs focusing on hydrogen FCEVs with the above matters in mind. More specifically, an examination of the FCEV technology and their prospective worldwide is investigated in this work.

Optimization of the Delivery Time within the Distribution Network, Taking into Account Fuel Consumption and the Level of Carbon Dioxide Emissions into the Atmosphere

The evolution of changes in shopping in the modern society necessitates suppliers to seek new solutions consisting of increasing the efficiency of transport processes. When it comes to controlling the flow of goods in modern distribution networks, planning and timely deliveries are of particular importance. The first factor creating a competitive advantage involves the tendency to shorten order delivery times, especially for products with a short shelf life. Shorter delivery times, in turn, extend the period of effective residence of the product “available on the shelf”, increasing the likelihood of its sale. The second component in line with the Sustainable Development Strategy consists of aspects related to the protection of the natural environment, in particular those related to car transport. In this case, the fuel consumption and the level of emitted toxic substances (including carbon dioxide) are analyzed and assessed. Bearing in mind the above, this article presents the problem of optimizing the delivery time within the assumed distribution network and its solution, enabling the company to develop and optimal plan for the transport of products with a short shelf life. The paper proposes a model that takes into account minimization of the delivery time, while estimating the values of fuel consumption and CO2 emissions for the variants considered. The means of transport were medium-duty trucks. Three variants of the assumptions were considered, and algorithms implemented in MS Excel and MATLAB software were used to perform the optimization. Using the MATLAB environment, a more favorable value of the objective function was obtained for the variant without additional constraints. On the other hand, the algorithm implemented in MS Excel more effectively searched the set of acceptable solutions with a larger number of constraining conditions.

Charging Infrastructure for Electric Vehicles Considering Their Integration into the Smart Grid

Concern about environmental problems, including the greenhouse effect, directly related to the gases produced by vehicles, has led governments and various organizations to promote standards on fuel use and gas emissions. Therefore, promoting the development of electric vehicles is fundamental to facing the challenges of climate change and achieving sustainable transportation. For this reason, this article presents a bibliometric analysis based on databases to elaborate on the state of the art that integrates successful cases in the design and implementation of charging stations for electric vehicles. Once the results are presented, a methodological model is proposed for the design of charging stations considering restrictions and recommendations issued by international standardization organizations. The Digsilent PowerFactory software analyzes the behavior of active and reactive power, voltage, and current. Finally, a system for different charging modes and powers is proposed. The charging system is tested through the insertion of phase–ground, phase–phase, and three-phase short circuits located at the connection points of the charging stations, and the faults are inserted and released in different periods for the analysis of system stability. As a result, it has a stable system for all proposed scenarios, as long as the fault is released; otherwise, the system remains unstable. The three-phase fault is the most severe for the load system, making the performance of the protections assigned to each circuit essential.

Experimental Studies of the Effect of Air Filter Pressure Drop on the Composition and Emission Changes of a Compression Ignition Internal Combustion Engine

This paper presents an experimental evaluation of the effect of air filter pressure drop on the composition of exhaust gases and the operating parameters of a modern internal combustion Diesel engine. A literature analysis of the methods of reducing the emission of toxic components of exhaust gases from SI engines was conducted. It has been shown that the air filter pressure drop, increasing during the engine operation, causes a significant decrease in power output and an increase in fuel consumption, as well as smoke emission of Diesel engines with the classical injection system with a piston (sectional) in-line injection pump. It has also been shown, on the basis of a few literature studies, that the increase in the resistance of air filter flow causes a change in the composition of car combustion engines, with the effect of the air filter pressure drop on turbocharged engines being insignificant. A programme, and conditions of tests, on a dynamometer of a modern six-cylinder engine with displacement Vss = 15.8 dm3 and power rating 226 kW were prepared, regarding the influence of air filter pressure drop on the composition of exhaust gases and the parameters of its operation. For each technical state of the air filter, in the range of rotational speed n = 1000–2100 rpm, measurements of exhaust gas composition and emission were carried out, as well as measurements and calculations of engine-operating parameters, namely that of effective power. An increase in the pressure drop in the inlet system of a modern Diesel truck engine has no significant effect on the emissions of CO, CO2, HC and NOx to the atmosphere, nor does it cause significant changes in the degree of smoke opacity of exhaust gases in relation to its permissible value. An increase in air filter pressure drop from value Δpf = 0.580 kPa to Δpf = 2.024 kPa (by 1.66 kPa) causes a decrease in the maximum filling factor value from ηυ = 2.5 to ηυ = 2.39, that is by 4.5%, and a decrease in maximum power by 8.8%.

Interaction of Consumer Heterogeneity and Technological Progress in the US Electric Vehicle Market

Electric Technology Vehicles (ETVs: hybrid, electric, and plug-in hybrid) may reach price parity with incumbent internal combustion vehicles (ICEVs) in the near future. Climate policy for transportation will depend on the degree to which consumers prefer ETVs, and price parity is a key factor. In this study, we explore the interaction between future cost reductions and the economically motivated adoption of ETVs. We construct a model of the U.S. personal vehicle market accounting for heterogenous use and vehicle preferences, in which adoption induces cost reductions that increase future market share. Model results indicate that price parity is reached for most consumers in a number of cost scenarios, but not with constant ICEV costs and modest ETV cost declines. A price parity future suggests that government support could be temporary and phased out after a successful market transition. However, if ETVs continue to be more expensive than ICEVs, then lasting government support is needed. Heterogeneity is essential to understanding the market transition: treating consumers as heterogeneous results in an ETV market share 23% higher than assuming average consumers. Future work can clarify ETV support policy by resolving uncertainty in cost trajectories and modeling dynamic and heterogenous consumer markets.

A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks

The topic of power loss reduction in distribution systems has gained significant attention over recent years. Despite the efforts of the European Union towards the minimization of power losses, the decarbonization of the transport sector has raised several concerns, since charging overlaps of Electric Vehicles (EVs) can cause extensive power losses and power quality issues. Considering these, the present paper proposes a two-stage EV charging planning and Network Reconfiguration (NR) methodology, addressing the problem of power loss minimization in both Low-Voltage (LV) and Medium-Voltage (MV) Distribution Networks (DNs), respectively. In the first stage, considering the key role of the aggregator, the EV charging planning is applied to LV DN. In the second stage, the NR technique is applied to the MV DN, by taking into account the hourly power demand of LV DNs as obtained by the aggregators. The proposed methodology has been applied on a benchmarked MV network for which each node is represented by a real LV network. The results indicate that the proposed methodology could yield up to a 63.64% power loss reduction, in respect to the base scenario, i.e., no charging planning and no NR are applied.

An Electric Fence-Based Intelligent Scheduling Method for Rebalancing Dockless Bike Sharing Systems

With a new generation of bike sharing services emerging, the development of dockless bike sharing services results in considerable socioeconomic and environmental benefits but also creates new issues, such as inappropriate parking behaviors and bike imbalances. To solve the inappropriate parking problem, electric fences have been introduced to guide users to park bikes in designated zones. Considering the role of electric fences in restricting user parking behaviors, an electric fence-based intelligent scheduling method for rebalancing dockless bike sharing systems is proposed in this paper. As a dynamic method that considers the real-time usage of bike sharing systems, an electric fence adjusts its capacity based on real-time information, which guides users to return bikes to electric fences with greater urgency. Because existing approaches require prespecified models and are unable to consider all the intricacies in the dynamic optimization problem, a model-free intelligent scheduling approach based on deep Q-learning that can adapt to the changing distributions of customer arrivals, available bikes, bike locations, and user travel times is used to solve the problem. Finally, a case study involving Beihang University is employed, which shows that the method performs well in rebalancing the bike sharing system and improving the mean utilization (MU) and customer satisfaction (CS).

Household Ability of Expenditures on Electricity and Energy Resources in the Countries That Joined the EU after 2004

The purpose of the following article is to present the situation of the energy market from a household perspective between 2010 and 2020 in selected EU countries (the group of member states which joined EU after 2004). The selected countries when joining the EU had similar economic indicators and to some extent were similar in other macro-economic situations (personal income, unemployment rate, GDP level and annual growth). This article analyzes the past and current situation of the household ability expenditure on electricity and energy resources (petrol—eurosuper 95 and diesel and natural gas), taking into account price, tax conditions and the real possibility to purchase the analyzed energy sources (based on annual net salaries). The paper includes the conclusions and prospects for the future. The main objective of the study is to determine the ability amount of expenditure on electricity, natural gas and liquid fuels by household in the countries that joined the European Union after 2004. The specific objectives of the work include: the evolution of retail prices of energy sources in those countries and prices of electricity, natural gas and liquid fuels—petrol and diesel oil—in the research period from 2010 to 2020. The element that influences the final price, as assessed in this paper, is the share of taxes and compulsory charges imposed by the EU countries covered in this study. The result of the study presented inter alia that energy consumption structure did not change significantly, electricity prices were steadily growing in the countries under assessment, the use of liquid fuels—petrol and diesel oil—in the countries under study, grew over the study period. Furthermore, prices of fuel fluctuated over the period from 2010 to 2020 and during the COVID-19 pandemic, which broke out in March 2020, but did not cause any significant changes in the prices of energy carriers in the analyzed period, apart from the declines in the prices of eurosuper 95 and diesel.

Numerical and Thermal Investigation of Magneto-Hydrodynamic Hybrid Nanoparticles (SWCNT-Ag) under Rosseland Radiation: A Prescribed Wall Temperature Case

Thermal heat generation and enhancement have been examined extensively over the past two decades, and nanofluid technology has been explored to address this issue. In the present study, we discuss the thermal heat coefficient under the influence of a rotating magneto-hydrodynamic hybrid nanofluid over an axially spinning cone for a prescribed wall temperature (PWT) case. The governing equations of the formulated problem are derived by utilizing the Rivlin–Ericksen tensor and boundary layer approximation (BLA). We introduce our suppositions to transform the highly non-linear partial differential equations into ordinary differential equations. The numerical outcomes of the problem are drafted in MATLAB with the of help the boundary value problem algorithm. The influences of several study parameters are obtained to demonstrate and analyze the magneto-hydrodynamic flow characteristics. The heat and mass transfer coefficients increase and high Nusselt and Sherwood numbers are obtained with reduced skin coefficients for the analyzed composite nanoparticles. The analyzed hybrid nanofluid (SWCNT-Ag–kerosene oil) produces reduced drag and lift coefficients and high thermal heat rates when compared with a recent study for SWCNT-MWCNT–kerosene oil hybrid nanofluid. Maximum Nusselt (Nu) and Sherwood (Sh) numbers are observed under a high rotational flow ratio and pressure gradient. Based on the results of this study, we recommend more frequent use of the examined hybrid nanofluid.

Electric Vehicles: Bibliometric Analysis of the Current State of the Art and Perspectives

In order to gain a comprehensive view of electric vehicles (EVs) technologies and understand the emphasis of current research, this study evaluated the most relevant themes related to EVs through a bibliometric analysis using the keyword “electric vehicle” as the input. The Web of ScienceTM (WoS) database was used because it is considered ideal for bibliometric analysis. The VOSviewer software was adopted as a bibliometric analysis tool to visualize the networks of authors, countries, journals and keywords. The analysis carried out on 9 November 2021 retrieved a total of 29,304 documents in the period 2000 to 2021. The results show that in the last nine years the number of publications about EVs has grown significantly. The China is the leading nation in the field of EV research, contributing the largest number of publications in the world, with the main authors and research institutions involved. The journal Energies stands out as the main publishing periodical. Keyword analysis showed that studies on EVs in the last two decades have focused on themes related to energy management and storage, infrastructure and charging systems and environmental issues. The bibliometric analysis presented provides relevant information on the main themes studied about EVs and technological advances in development.

Development of Electromobility in European Union Countries under COVID-19 Conditions

The introduction of electromobility contributes to an increase in energy efficiency and lower air pollution. European countries have not been among the world’s leading countries in this statistic. In addition, there have been different paces in the implementation of electromobility in individual countries. The main purpose of this paper is to determine the directions of change and the degrees of concentration in electromobility in European Union (EU) countries, especially after the economic closure as a result of the COVID-19 pandemic. The specific objectives are to indicate the degree of concentration of electromobility in the EU and changes in this area, especially during the COVID-19 pandemic; to determine the dynamics of changes in the number of electric cars in individual EU countries, showing the variability in this aspect, while also taking into account the crisis caused by COVID-19; to establish the association between the number of electric cars and the parameters of the economy. All EU countries were selected for study by the use of the purposeful selection procedure, as of December 31, 2020. The analyzed period covered the years 2011–2020. It was found that in the longer term, the development of electromobility in the EU, measured by the number of electric cars, is closely related to the economic situation in this area. The crisis caused by the COVID-19 pandemic has influenced the economic situation in all EU countries, but has not slowed down the pace of introducing electromobility, and may have even accelerated it. In all EU countries, in the first year of the COVID-19 pandemic, the dynamics of introducing electric cars into use increased. The growth rate in the entire EU in 2020 was 86%, while in 2019 it was 48%. The reason was a change in social behavior related to mobility under conditions of risk of infection. COVID-19 has become a positive catalyst for change. The prospects for the development of this type of transport are very good because activities related to the development of the electromobility sector perfectly match the needs related to the reduction of pollution to the environment.

The Development of Electromobility in the European Union: Evidence from Poland and Cross-Country Comparisons

The article presents the current situation with the implementation of electric cars in Poland against the background of pan-European trends and the current energy sector condition in Poland. The aim of the study was to show the ecological, economic, social, and technical difficulties and controversies related to the use of electric cars in Poland. The authors used statistical analysis and identified the main factors of electromobility development in Poland. Despite the declared electromobility in the Strategy of Responsible Development program, the degree of its implementation is far from the previously established goals. The article analyzes the feasibility of the above plan and indicates the factors inhibiting the development of electromobility in Poland. The strategy and decisions to further implement electric cars cannot be purely political. In justifying the need to promote the use of electric cars in Poland, one should take into account the specificity of the Polish economy, its energy system, the condition of its infrastructure, and real social needs. The authors formulated a hypothesis that the aforementioned program is based on simplistic assumptions and marginalizes or ignores significant barriers to the development of electricity-based transport in Poland. The successful implementation of that program is conditioned by comprehensive and costly activities aimed to transform the whole energy system and introduce an effective system of incentives for the buyers of electric cars.

Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Although Industry 4.0 has received much attention in recent years due to the possibility of increasing companies’ productivity, the implementation process is complex. The aim of this study is to present a holistic model for implementing Industry 4.0 based on cleaner production as a fundamental tool for the development of production systems that meet the Sustainable Development 04026-002Goals (SDGs), and social stakeholders that cooperate with this implementation process, helping to develop sustainable infrastructure, processes and technologies to increase the sustainable transformation of these companies towards Industry 4.0. The method used was literature research, and the Delphi technique was used to ask specialists to contribute with their experience to evaluate and propose improvements to the model, in the form of a consensus. The model contributes to the Sustainable Development Goals 9, 12 and 15. This holistic and sustainable model is a contribution to theory and practice, helping executives, technicians, entrepreneurs and those involved with Industry 4.0 to base the implementation process in the needs and specificities of each company, avoiding the “one fits all” models, considering the peculiarities of each company and the complexity of the implementation process in a more efficient and collaborative digital production ecosystems base, seeking to reduce inequalities, through the joint effort of social stakeholders to find ways to restore and/or improve social harmony, impacted by Industry 4.0.

The Potential of Using Renewable Energy Sources in Poland Taking into Account the Economic and Ecological Conditions

The aim of the manuscript was to present the collective results of research on the profitability of using various renewable sources in Poland with the greatest development potential. In the paper, the economic parameters of various investment projects were determined and calculated, i.e., Net Capital Value (NPV), Internal Rate of Return (IRR) and the Period of Return on Invested Capital (PBT). The economic assessment of the use of RES technologies was supplemented with the assessment of environmental benefits. The ecological criterion adopted in the study was the assessment of the potential and costs of reducing greenhouse gas emissions as a result of replacing fossil fuels with renewable energy technologies. On the basis of the constructed economic model to assess the profitability of investments, it has been shown that the analyzed projects will start to bring, depending on their type and technical specification, measurable economic benefits in the form of a reduction in the amount of energy purchased on an annual basis and environmental benefits in the form of reduction of carbon dioxide emissions to the atmosphere. Moreover, the calculations show a high potential for the use of certain renewable sources in Poland, which contributes to the fulfillment of energy and emission obligations towards the EU. The analyzes and research of the Polish energy market with the use of the presented models have shown that the project is fully economically justified and will allow investors to make a rational decision on the appropriate selection of a specific renewable energy source for their investment. The presented economic models to assess the profitability of investments in renewable energy sources can be successfully used in other countries and can also be a starting point for a discussion about the direction of energy development. Due to the lack of collective, original and up-to-date research on the domestic market, the manuscript provides the reader with the necessary knowledge regarding the legitimacy of using renewable energy sources, investment and environmental profitability.

Multi-Channel Profile Based Artificial Neural Network Approach for Remaining Useful Life Prediction of Electric Vehicle Lithium-Ion Batteries

Remaining useful life (RUL) is a crucial assessment indicator to evaluate battery efficiency, robustness, and accuracy by determining battery failure occurrence in electric vehicle (EV) applications. RUL prediction is necessary for timely maintenance and replacement of the battery in EVs. This paper proposes an artificial neural network (ANN) technique to predict the RUL of lithium-ion batteries under various training datasets. A multi-channel input (MCI) profile is implemented and compared with single-channel input (SCI) or single input (SI) with diverse datasets. A NASA battery dataset is utilized and systematic sampling is implemented to extract 10 sample values of voltage, current, and temperature at equal intervals from each charging cycle to reconstitute the input training profile. The experimental results demonstrate that MCI profile-based RUL prediction is highly accurate compared to SCI profile under diverse datasets. It is reported that RMSE for the proposed MCI profile-based ANN technique is 0.0819 compared to 0.5130 with SCI profile for the B0005 battery dataset. Moreover, RMSE is higher when the proposed model is trained with two datasets and one dataset, respectively. Additionally, the importance of capacity regeneration phenomena in batteries B0006 and B0018 to predict battery RUL is investigated. The results demonstrate that RMSE for the testing battery dataset B0005 is 3.7092, 3.9373 when trained with B0006, B0018, respectively, while it is 3.3678 when trained with B0007 due to the effect of capacity regeneration in B0006 and B0018 battery datasets.

Low Carbon Scenario Analysis of a Hydrogen-Based Energy Transition for On-Road Transportation in California

Fuel cell electric vehicles (FCEV) are emerging as one of the prominent zero emission vehicle technologies. This study follows a deterministic modeling approach to project two scenarios of FCEV adoption and the resulting hydrogen demand (low and high) up to 2050 in California, using a transportation transition model. The study then estimates the number of hydrogen production and refueling facilities required to meet demand. The impact of system scale-up and learning rates on hydrogen price is evaluated using standalone supply chain models: H2A, HDSAM, HRSAM and HDRSAM. A sensitivity analysis explores key factors that affect hydrogen prices. In the high scenario, light and heavy-duty fuel cell vehicle stocks reach 12.5 million and 1 million by 2050, respectively. The resulting annual hydrogen demand is 3.9 billion kg, making hydrogen the dominant transportation fuel. Satisfying such high future demands will require rapid increases in infrastructure investments starting now, but especially after 2030 when there is an exponential increase in the number of production plants and refueling stations. In the long term, electrolytic hydrogen delivered using dedicated hydrogen pipelines to larger stations offers substantial cost savings. Feedstock prices, size of the hydrogen market and station utilization are the prominent parameters that affect hydrogen price.

A Method of Analyzing the Residual Values of Low-Emission Vehicles Based on a Selected Expert Method Taking into Account Stochastic Operational Parameters

Increasing the market share of low-emission vehicles in relation to individual mobility is one of the main postulates of modern transport policy. In the discussion on low-emission and the new structure of the car fleet, the role of new vehicles is emphasized above all, ignoring the importance of the secondary market. In recent years, both in Poland and in other European Union countries, there has been a noticeable dynamic development of electromobility implementation processes in urban areas, the initial effect of which is increasing market accessibility to commercial vehicles with electric EV/BEV, hybrid HEV/PHEV and fuel cell powered FCEV. As in the case of vehicles powered by conventional ICEV fuels, also in relation to those defined as low-emission, their residual value is lost along with the operational process. Information on this variable is important both for the owner of a newly purchased vehicle, which after the period of its operation will decide to sell it as well as to the future buyer. The scientific aim of the study is to analyze the residual values of selected vehicle models from the primary and secondary market, with particular emphasis on stochastic operational phenomena. The subject of the research is to obtain extensive knowledge on the achieved changes in the residual values of low-emission vehicles in relation to ICEVs. For this purpose, a comparative analysis of the commercial program, data approximated from auction portals and own numerical modeling tool based on a neural network was performed. The research sample included, among others, selected models of passenger cars, the purchase offer of which included the choice of a drive unit powered by conventional and low-emission fuels. The use of this method allowed to answer the question whether low-emission vehicles are characterized by a greater or lesser loss of value in relation to conventionally powered vehicles ICEV.

Infrastructure Planning for Autonomous Electric Vehicles, Integrating Safety and Sustainability Aspects: A Multi-Criteria Analysis Approach

After the awareness-raising of recent years for coping with the global societal, economic and environmental challenges, the need for sustainable planning in the transport sector has become even more evident. Initiatives aiming at promoting sustainable and innovative mobility solutions, especially in urban areas where mobility needs are higher and transport problems are more intense, have been launched by different organizations around the world. In this context, autonomous electric vehicles are emerging as a promising solution; however, they are accompanied by new infrastructure requirements, along with safety concerns. Policymakers will be confronted with an array of choices, such as plug-in or wireless, dynamic or stationary charging and mixed flow with conventional vehicles or dedicated lanes, taking into account the uncertain impacts of innovation on safety and sustainability. Within this scope, these infrastructure alternatives are evaluated and prioritized, for the first time, in the present study, through the combined application of two hybrid multi-criteria analysis models, with the participation of experts. The analysis is based on a set of safety and sustainability criteria. Road safety and exposure to electromagnetic radiation emerge as the most important criteria, with the optimum solution—based on current data—consisting of plug-in charging and the circulation of autonomous electric vehicles in dedicated lanes.

Cost and Environmental Impacts of a Mixed Fleet of Vehicles

Urban parcel delivery is increasingly restricted by regulations limiting access to certain heavy or high emitting vehicles to reduce emissions and noise pollution in cities. Cargo bikes represent an alternative solution that enables deliveries with low environmental impact, but they may represent a higher economic cost and come with constraints like battery autonomy or small loading capacity. As a transport scheme relying on bikes for the last miles with fewer externalities, it is regarded as an environmentally friendly choice, and economic sustainability is assessed. This paper aims to present the environmental and economic aspects of different delivery means of transport in European urban areas. Life cycle assessment (LCA) methodology is selected to analyse the environmental impact of several vehicles, allowing us to quantify the emissions according to the loading factor. The electricity mix is an important parameter and makes the results vary according to the country studied. For the economic aspect, the cost price allows us to quantify the operational cost of each means of transport. A trade-off can thus be made between the two.

The Economic Aspect of Using Different Plug-in Hybrid Driving Techniques in Urban Conditions

Plug-in hybrids (PHEV) have become popular due to zero-emission driving, e.g., in urban areas, and using an internal combustion engine on longer distances. Energy consumption by the PHEV depends on many factors which can be either dependent or independent of the driver. The article examines how the driver can use the vehicle’s capabilities to influence its wear. Determining the optimal driving technique, due to the adopted nature of the timetable, is the basic variable that determines the profitability of using a given drive system. Four driving techniques have been selected to determine which one can offer the largest advantages. A vehicle-dedicated application has recorded the drivetrain performance on a predetermined route through an urban area. The analysis of results has demonstrated which of the driving techniques provides measurable effects in terms of reduced energy consumption and the shortest travelling time. The study shows longitudinal acceleration and torque generated by the electric drive. The information included in the study can help any PHEV user reduce the operating cost by applying an appropriate driving technique. The proposed research introduces the possibilities of assessing the influence of the driving style on energy consumption. The innovative side of this research is the observation of stochastic phenomena that are difficult to detect when using approximation modelling.

A Component-Sizing Methodology for a Hybrid Electric Vehicle Using an Optimization Algorithm

Many leading companies in the automotive industry have been putting tremendous effort into developing new powertrains and technologies to make their products more energy efficient. Evaluating the fuel economy benefit of a new technology in specific powertrain systems is straightforward; and, in an early concept phase, obtaining a projection of energy efficiency benefits from new technologies is extremely useful. However, when carmakers consider new technology or powertrain configurations, they must deal with a trade-off problem involving factors such as energy efficiency and performance, because of the complexities of sizing a vehicle’s powertrain components, which directly affect its energy efficiency and dynamic performance. As powertrains of modern vehicles become more complicated, even more effort is required to design the size of each component. This study presents a component-sizing process based on the forward-looking vehicle simulator “Autonomie” and the optimization algorithm “POUNDERS”; the supervisory control strategy based on Pontryagin’s Minimum Principle (PMP) assures sufficient computational system efficiency. We tested the process by applying it to a single power-split hybrid electric vehicle to determine optimal values of gear ratios and each component size, where we defined the optimization problem as minimizing energy consumption when the vehicle’s dynamic performance is given as a performance constraint. The suggested sizing process will be helpful in determining optimal component sizes for vehicle powertrain to maximize fuel efficiency while dynamic performance is satisfied. Indeed, this process does not require the engineer’s intuition or rules based on heuristics required in the rule-based process.