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.

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

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.

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

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.

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

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.

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

Transportation is the second-largest sector contributing to greenhouse gas emissions due to CO2 gas generation from the combustion of fossil fuels. Electric vehicles (EVs) are believed to be a great solution to overcome this issue. EVs can reduce CO2 emissions because the vehicles use an electric motor as a propeller instead of an internal combustion engine. Combined with sustainable energy resources, EVs may become zero-emission transportation. This paper presents an overview of the EV drive train types, including their architecture with the benefits and drawbacks of each type. The aim is to summarize the recent progress of EV technology that always continues to be updated. Furthermore, a comparative investigation on energy density and efficiency, specific energy and power, cost, and application is carried out for batteries as the main energy storage. This discussion provides an understanding of the current development of battery technology, especially the batteries used in EVs. Moreover, the electric motor efficiency, power density, fault tolerance, reliability, and cost are also presented, including the most effective electric motor to use in EVs. The challenges and opportunities of EV deployment in the future are then discussed comprehensively. The government regulation for EVs is still a major non-technical challenge, whereas the charging time and battery performance are the challenges for the technical aspect.

A Review on Drive Train Technologies for Passenger Electric Vehicles

Electromobility is a growing technology for land transport, constituting an important element of the concept of sustainable economic development. The article presents selected research results concerning one of the segments of this market-vehicles powered by hydrogen fuel cells. The subject of the research was to gain extensive knowledge on the economic factors influencing the future purchasing decisions of the demand side in relation to this category of vehicles. The research was based on a numerical experiment. For this purpose, a comparative analysis of purchase prices in relation to the TCO of the vehicle after 3–5 years of use was performed. The research included selected models that are powered by both conventional and alternative fuels. The use of this method will allow to assess the real costs associated with the hydrogen vehicle. The authors emphasize the important role of economic factors in the form of the TCO index for the development of this market. The experimental approach may be helpful in understanding the essence of economic relations that affect the development of the electro-mobility market and the market demand for hydrogen fuel cell-powered vehicles in Poland.

https://www.mdpi.com/1996-1073/14/8/2131/pdf

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

The article presents the methodology of isolating aperiodic phenomena constituting the basis of the energy balance of vehicles for the analysis of electromobility system indicators. The symptom observation matrix (SOM) and experimental input data are used to analyze periodic phenomena symptoms. The multidimensional nature of the engine efficiency shortage has been well defined and analyzed in terms of errors in the general model using neural networks, singular value decomposition, and principal component analysis. A more difficult task is the analysis of a multidimensional decision-making process. The research used a data fusion method and the concept of symptom reliability, which is applied to the generalized failure symptom obtained by applying the singular value decomposition (SVD). The model research has been based on the gray system theory (GST) and GM forecasting models (1,1). Input data were obtained from the assessment of driving cycles and analysis of the failure frequency for 1200 vehicles and mileage of 150,000 km. Based on this analysis, it can be concluded that with the current infrastructure and operating costs and the frequency of failure of PHEV and BEV drives, ICEV vehicles are unrivaled in terms of their operating costs.

Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas

Purpose: The article presents selected research results concerning the Polish path of electromobility development. The subject of the research was to gain extensive knowledge about contemporary consumer attitudes. This goal was achieved by trying to identify the most important factors determining the choice of electric vehicles by the demand side in the Polish automotive market. Approach / Methodology / Design: CAWI techniques were used in the study. The study was conducted at the turn of 2020 and 2020. The research sample included 1,000 respondents - current owners of conventional fuel vehicles. Conclusions: Increasing the share in the electric vehicle market is one of the pillars of the electromobility development program in Poland. The authors emphasize the essence of the relationship between consumers' attitudes towards electric vehicles and the willingness to buy them and continue to use them. Practical implications: The study shows that the knowledge of consumer attitudes plays an important role in the development program electromobility in Poland. By verifying opinions about electric vehicles among their potential buyers. Originality/Value: The survey attempts to fill a gap in the literature on the subject. An experimental research approach may clarify the essence of the relationship between the development of electromobility and the attitude of consumers.

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Piotr Wróblewski

Papers

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

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

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

Methodology for Assessing the Impact of Aperiodic Phenomena on the Energy Balance of Propulsion Engines in Vehicle Electromobility Systems for Given Areas

The Road to Electromobility in Poland: Consumer Attitude Assessment