The range of issues related to electromobility is relatively broad. It is generally reported to be an area of transport that has strong dynamics. This dynamic results from the transformation of the automotive industry, which is largely influenced by international initiatives such as the Paris Agreement, from the conclusions of which the Green New Deal and European Green Deal were formulated. The core of the transformation is the transition from combustion engines and electric engines (or other alternatives to gasoline-powered engines).
As already mentioned, electromobility is influenced by global and local factors. Each of the identified factors can be reformulated into keywords (KW) that are suitable for the implementation of the first step of SLR. Some factors were not transformed into KWs due to their generality, which would harm article searches. The negative impact would be that articles that are explicitly outside the topic of this article would be included in the search result.
Other search parameters were related to year limits. If the purpose of the conducted research is to characterise trends in electromobility, the time frame included in the search is from 2021 to the present. We assume that the period of the last two years sufficiently captures the latest scientific outputs, from which it is possible to formulate electromobility trends.
A specific area of inquiry is important for the reason that if businesses providing or dealing with electromobility are successful in the market, it is necessary to analyse their market position or characteristics of the market in which they operate. If it is clear what laws apply in the market, the company can adapt its offer to the trends that affect the given business segment. Data, about the market and services that are offered on the market, provide knowledge to policymakers that focus their activities on electromobility.
Thus, as other criteria for narrowing down the scope of identified articles, screening of titles of articles was carried out. The key for screening was whether the topic of the article is related to the areas of influence: value-added services and market characteristics, for which there are factors such as ICT-based services, multimodal concepts, private car sharing, long-time battery services, market penetration, and co-operation.
As a result of the screening, which involved a thorough analysis of the identified abstracts and article titles, the number of identified articles was reduced to 78 articles. From these articles further screening was needed because not every article was relevant to our research. Another screening, therefore, excluded another 30 articles, and the final number of articles, from which we derived data for our analysis, is 48.
3.1. Market Characteristics
Orfanou et al. (2021) [
20] summarise the electric vehicles (EVs) market (from the point of view of charging infrastructure, e-vehicle fleet, incentives, technology, campaigns, legislation, enforcement, education, research, and innovation). In their article, they state that the number of electric vehicles is still low, and not all European cities have made progress in this direction. There are indications that regions with significant progress in the field of electromobility should still elaborate a lot to increase their performance in most of the analysed aspects.
The past two years were significantly affected by the COVID-19 pandemic. Rokicki et al. (2022) [
21] state that even though the pandemic changed the economic situation in Europe, it has not slowed down the pace of introducing electromobility, and may have even accelerated it.
If the changes are related to the transition from internal combustion engines to electric, how long will this transition take? The answer to this question was dealt with by Rabiega et al. (2021) [
22] in their article which is a case study focusing on Poland. They state that if the goal is climate neutrality, which is to be achieved by 2050, then in 2050, approximately 30% of vehicles with combustion engines will still be on the road, which will lead to 80% reductions in emissions and an increase in demand for electricity and hydrogen (
Figure 1 and
Figure 2).
Šoltés et al. (2021) [
23] state that it is currently not demonstrable that there is an impact of electromobility on the reduction in greenhouse gas emissions at the national levels of EU countries. It is possible to assume that with the increase in the share of EVs on the roads (as stated in the study by Rabiega et al.), there will be a reduction in greenhouse gasses, which will also be read by aggregated statistics (Eurostat, OECD, etc.).
When achieving the set goals of reducing greenhouse gas emissions, the existing power grid will face challenges due to intermittency and the non-dispatchable nature of wind and solar energy production. Colmenar-Santos et al. (2021) [
24] came up with a solution in the form of a strategy based on a novel grid technique that is presented and evaluated for the optimal integrated operation of renewable resources and EVs to increase the penetration of renewable energy.
If enough EVs charge during peak hours, costly grid expansions may be needed. Wangsness et al. (2021) [
25] propose a new economic model for passenger transport in the greater Oslo area, where applying tariffs differentiated between peak and off-peak periods will help strike a better balance between grid investment costs and EV-owners’ disutility of charging during off-peak hours.
According to the study by Indonesian authors Alamsjah et al. (2021) [
26], four dimensions are currently key when choosing an EV (electric vehicle): socio-demographic, technical, economic, and behavioural (
Figure 3). Their study is regional and focuses on Indonesia.
According to the conclusions of the study, understanding of EVs is constructed dominantly based on information available online. The price of EVs, as well as tax incentives, is an influential factor affecting their intention of purchasing. From the perspective of EV performance, charging time to the vehicle fuel capacity of fewer than three hours is acceptable to the majority of the participants. SUV and city car types are preferable. The vehicle’s durability is also highly regarded. The intention to purchase an EV is influenced by the factors of age and education level but not by the factors of sex, marital status, or employment.
Another similar view is provided in a study by Bera and Maitra (2021) [
27] which provides the view of consumers in the Indian market toward the plug-in hybrid electric vehicle (PHEV). According to the findings of this study, charging time, battery warranty, and price are crucial when consumers decide whether or not to buy a PHEV. The same factors influencing consumers, as in the case of the Indian market, are found by Haidar and Rojas Aguilar (2022) [
28], Rosales-Tristancho and Carazo (2021) [
29], Kongklaew (2021) [
30], and Singh et al. (2021) [
31] with the difference that in the case of their study it is the French, Spanish, Thai and Indian markets. Hasan (2021) [
32], researching the Norwegian EV market, points to the fact that in addition to the battery, charging and price-related factors, environmental aspects associated with EVs are also important when purchasing them. Esteves et al. (2021) [
33] point to the fact that for Spanish consumers electric vehicles (EVs) represent a viable option to reduce ecological damage and improve public health.
The purchase of a classic car with an internal combustion engine is often influenced by the reliability of the car, which takes the form of not only the low failure rate of the vehicle but also the driving range. As pointed out by Higueras-Castillo (2021) [
34], Rotaris et al. (2021) [
35] (in the case of the Slovenian and Italian markets, respectively), and Skowrońska-Szmer and Kowalska-Pyzalska (2021) [
36] (in the case of Polish market) the same factors influence the purchase of EVs.
Rommel and Sagebiel (2021) [
37] point to another important factor, which is the availability of charging stations. Their research focused on the German market, where a fundamental finding is the indication of low preferences for battery electric vehicles for consumers, who are house owners in sub-urban regions. This consumer group, as a potential representative of the middle-class, can be characterised as ideal for future EV purchases. Therefore, marketing efforts should be more focused on this consumer group.
Zimm (2021) [
38] states that great discrepancies exist across countries regarding EV support and uptake. EV diffusion is conceptualised as an outcome of policy diffusion based on national characteristics and international mechanisms.
Even so, studies by Baldursson et al. (2021) [
39] and Hasan and Mathisen (2021) [
40], implemented in Norway, the Netherlands, and China, point to the fact that if certain concessions are provided, consumers tend to think about electrifying their fleet of vehicles. Broadbent et al. (2022) [
41], from an analysis of the New Zealand EV market, reports similar findings: those who responded positively favoured incentives designed to affect purchase price reductions and increase nationwide fast-charger deployment of EVs. If incentives are a factor affecting whether consumers buy EVs, Macioszek (2021) [
42] states that the promotion of EVs in Poland should be centred around incentive programs. From the analysis of the Greek market, these findings are supplemented by Geronikolos and Potoglou (2021) [
43], who point out that incentives should be also considered for different socio-economic segments of the population to prevent inequalities and match their preferences. Similar findings are reported by Bitencourt et al. (2021) [
44], who state that high prices may still be the major barrier to EV diffusion in Brazil, keeping EVs inaccessible to the majority of the population.
If incentives, in the form of subsidies and various benefits from the state, are a motivator to buy an EV, then another incentive, according to Jreige et al. (2021) [
45] who analysed the Lebanon market, is increasing fuel taxes. According to Kunle and Minke (2022) [
46] (French, German and Norwegian markets), Sahoo et al. (2022) [
47] (Indian market), and Singh et al. (2021) [
48] (Indian market), when EVs are available in the market, regulatory incentives and policies have to match consumer preferences. Among direct subsidies, policies affecting the purchase price of EVs are identified as the most effective instrument. The analysis further prompts a duality between national incentives and local programs supporting EV adoption. Furthermore, Oryani et al. (2022) [
49] point out that in Iran even non-monetary policies are positively connected with the acceptance rate of EVs.
The discussion regarding electromobility focuses not only on EVs but also on other areas connected with electromobility, such as electric roadways (ER), electric buses, and electric scooters. According to Konstantinou et al. (2021) [
50], currently, in the USA, public acceptance in general seems to be related to charging patterns, the safety of commute routes, and safety concerns for ERs among other factors, and depends on the implementation time of the technology. Pietrak and Pietrak (2021) [
51], in their study that took place in Poland, state that economic benefits resulting from implementing zero-emission buses in an urban transport fleet are limited by the current energy mix structure of the given country. An unfavourable energy mix may lead to increased emissions of SO2 and CO
2 resulting from the operation of this type of vehicle. Therefore, achieving full effects in the field of electromobility in the given country depends on taking concurrent actions to diversify the power generation sources. Vallejo-Morales et al. (2021) [
52] state that sales of e-scooters and e-scooter sharing services in Spain are growing. Perceived value, security, and technophilia (strong enthusiasm for technologies) are the main determinants of intentions to use and buy e-scooters.
3.2. Value-Added Services
If EVs are to successfully penetrate the market, EV-related services with added value must be provided. It can be assumed that these services bring additional value not only for consumers but also for producers in the form of information that can be used in other business-related activities.
Coban et al. (2022) [
53], in their case study which focuses on the area of present-day Turkey, state that electric road construction appears to be a low-cost alternative to the current road construction trend. If a large battery is replaced with a smaller battery for each new vehicle sold, after three years, enough savings will be made to electrify all highways and main roads in Turkey.
New possibilities brought by electromobility can significantly reduce external costs generated by transport by incorporating rail transport into the urban delivery systems. According to the case study by Pietrak et al. (2021) [
54], which took place in Poland’s Szczecin, this reduction is possible by using the LFR electric trains. Furthermore, another advantage of the adoption of electric trains is the reduction in negative effects generated by urban freight transport, which leads to achieving a coherent zero-emission system for handling cargo and passenger flows in cities.
Electromobility brings new possibilities for building intelligent integrated infrastructures connecting energy, transport, and urban infrastructure. Vilathgamuwa et al. (2022) [
55], researching this issue, created a proposal for the mobile-energy-as-a-service (MEaaS) concept for system-wide integration of energy, transport, and urban infrastructures for sustainable electromobility in cities (
Figure 4).
The proposal takes into account measures of optimal real-time power grid operationality, where different electricity demand scenarios should be modelled for different times of the day, considering the customer behaviour influenced by electricity price, mobility trip purpose, time, and customer convenience. Taking these aspects into account, the model focuses on what principles and rules encompassing transport, power, and civil engineering aspects should apply to in the context of cities. An important part of the model is the development of flexible incentive-based pricing mechanisms for MEaaS (where this involves optimal bidirectional charging through V2X/X2V of mobile/stationary EVs).
According to one of the most recent studies by Patel et al. (2021) [
56], there is a trend of linking blockchain technology with EV charging systems. The model is designed in such a way that every time an EV owner charges their car, they must pay for the vehicle charging service electronically. These payments are secured using blockchain technology. This means that, in the case of this model, blockchain is used for communication between vehicles and charging stations.
The penetration of electromobility into the market requires the creation of new infrastructure. According to Geronikolos and Potoglou (2021) [
43], who dealt with the issue, the EVs market requires strategic allocation of public charging infrastructure and national coverage to enable electric vehicles to travel within and out of the urban core. To ensure this strategic allocation, electricity providers should ensure that the network would be able to withstand the increased electricity demand that the public charging points and electric vehicles would create.
From the point of view of the smart cities concept, Anthony (2021) [
57] points out that EVs can actively promote the development of a smart grid via two-way communication—vehicle-to-grid and grid-to-vehicle. This form of cooperation is key in the creation of smart city concepts. There are several options for providing EV charging services. Arif et al. (2021) [
58] go further and statethat to support grid reliability and to encourage consumers to buy and use EVs, parking lot owners should provide services on a basis of the vehicle-to-grid, grid-to-vehicle, parking lot-to-grid, and parking lot-to-vehicle.
According to Fernandez (2021) [
59] and their study, which focused on Spain, the most likely future transport electrification scenario is BEVs equipped with a higher battery capacity and, consequently, the increased installation of fast-charging facilities. A suitable strategy lies in the development of a charging network at the workplace, allowing a slow charging of batteries during working hours. This strategy is less commercially attractive but represents the best option from the perspective of low emissions and electric grid reinforcement.
Charging an electric car is one of the basic attributes of owning an electric car. Regarding charging, the driver may be interested in where they can charge their electric car, how long will charging take, and how much it will cost. Schulz and Rode (2022) [
60] studied whether public charging infrastructure drives battery electric vehicle adoption. They analysed data for the years 2009 to 2019 and focused mainly on rural areas in Norway where a public charging network began to be built in selected years. They identified that ownership of electric cars increased by 200% in five years and therefore came to the conclusion that public charging infrastructure serves as a stimulus to the diffusion of battery electric vehicles.
Teoh (2021) [
61] dealt with the charging strategy of urban freight transport and proposed four unique charging strategy types: downtime, opportunity, intrusive, and emergency charging. Each charging strategy has a strong influence on the financial and operational performance of the transport operation and requires different types of charging systems and services to function. Downtime strategy is synonymous with in-house charging or overnight charging. Opportunity strategy is synonymous with destination charging. Intrusive charging happens when vehicle users want to charge it quickly during long or mid trips or commutations. Emergency charging is when a driver is alerted to a particular condition of the battery level while driving.
The importance of the charging infrastructure was the subject of the article by Li et al. (2021) [
62]. The findings of this article formulate a way for finding an optimal charging station location for EVs. Their work uses an improved genetic algorithm to locate public charging stations by considering the investment of charging station operators and the travel costs of battery electric vehicle owners. The methodology they proposed uses the multi-population genetic algorithm to provide more feasible allocations for public charging stations and according to their calculations, it could reduce total costs by 7.6%.
We have to look at charging an electric vehicle not only from the driver’s point of view but also from the point of view of the impact on the electric network charging electric cars. Authors Shibl et al. (2021) [
63] emphasise the importance of electric vehicle charging management since the charging of a high number of EVs harms the distribution system. They have contrasted many machine learning algorithms and they picked the most reliable that will minimise power losses and voltage fluctuations and achieve peak performance by flattening the load curve and also minimise the costs.
The Greek scientists Karapidakis et al. (2021) [
64] examined the hosting capacity of the power network in the metropolitan area of the capital city of Crete island—Heraklion. Greece is in an early stage of EV adoption, but they are already using significant incentives, which aim to subsidise the purchase of EVs and chargers to install 1000 new charging stations in the next few years and 10,000 charging points in the medium term. The research showed that the hosting capacity of charging EVs in the power grid of the city of Heraklion is 3862 slow-charging EVs that could simultaneously be charged under an average charging profile by the city’s grid infrastructure, even at the N-1 criterion of all the transformers. On the other hand, the number of fast charging EVs is considerably lower at 2316. At peak demand, when all the transformers work properly, the grid can simultaneously host 6993 EVs, mainly in the slow and medium-charge modes.
The management of the charging of electric vehicles was the scope of the research conducted by Kriukov et al. (2021) [
65]. The first article proposed a decentralised EV charging control (DEV-CC) system that can be executed by the existing on-board electronic control units (ECUs) and used dedicated short-range communication (DSRC) to establish communication between EVs. The proposed DEV-CC adapts the EV charging power depending on the low-voltage distribution network (LVDN) voltage levels measured by the EVs themselves. The main purpose of the proposed DEV-CC was to charge all the EVs connected to the LVDN without allowing the voltage to drop below the imposed limit. As the results of the article showed, the proposed DEV-CC manages to charge all EVs while maintaining the voltage levels within the LVDN above the allowable limits. The proposed DEV-CC does not require any investments from the distribution system operator (DSO), can be implemented on EVs with minimal costs, and is a viable solution to expensive smart grid systems.
The follow-up article by Kriukov and Gavrilas (2021) proposed and tested the behaviour of a novel decentralised EV charging control system (DEV-CC). In this paper, the response of the DEV-CC to variations in the power production of distributed generation (DG) sources is tested, and the results are compared to the results in the first paper mentioned above. The results showed that the DEV-CC system proposed in [
64] dynamically adapted to the variations in power produced by the DG sources. To adapt to these variations, DEV-CC did not require any additional improvements or any additional data to be acquired from the DG source or the grid [
66].
French authors Krim et al. (2021) [
67] assessed the role and benefits of photovoltaic (PV) for PV-powered charging infrastructures for EVs by better energy management. This management is performed by a microgrid based on PV panels installed on roofs or car parking shades, EV charging terminals, electrochemical stationary storage, and public grid connection. Their work aimed to define the economic aspects, feasibility, and preliminary requirements for this system, to avoid overloading the power grid and guarantee a higher percentage of clean energy. The proposed methodology was presented through the modelling and development of a techno-economic tool for local stakeholders, allowing them to manage and correctly size EV charging stations. It is divided into three phases. The first phase informs local stakeholders of the necessary space and the maximum sizing as well as the generated cost to install a PV-powered charging station (PVCS). During the second phase, the total cost of the PVCS is adjusted according to the users’ budgets and needs. The third phase presents a detailed qualitative analysis of the user-defined configuration. In this phase, the main objective is to assess the performance of the PVCS, and then, to improve its sizing and its operating modes aiming at increasing the use of PV energy, while minimizing energy supplied by the power grid. In addition, it allows evaluation of the PVCS performance by proposing an energy balance according to different charging scenarios (virtuous scenario, critical scenario, realistic scenario, and personalised scenario) and weather conditions. Moreover, this tool is reproducible in peri-urban areas since it can handle any location. Due to the tool’s manageability and simplicity compared to alternative calculation software, the tool is adjusted to be suitable for a wide spectrum of target groups, including experts and non-experts. The charging mode can influence the PV benefits, and the EVs can depend more/less on PV and the public grid. With a slow charging mode, the EVs can be charged mainly with PV energy and stationary storage systems. Whereas, in fast charging mode, EVs can be charged mainly with the public grid. The fast-charging mode can not only reduce PV benefits but also have an impact on the power grid and increase the electricity bills.