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Energy Reports 11 (2024) 4102–4114
Available online 8 April 2024
2352-4847/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Contents lists available at ScienceDirect
Energy Reports
journal homepage: www.elsevier.com/locate/egyr
Review article
Exploring the state of electric vehicles: An evidence-based examination of
current and future electric vehicle technologies and smart charging stations
Youness Hakam ∗, Ahmed Gaga, Benachir Elhadadi
Research Laboratory of Physics and Engineers Sciences (LRPSI), Research Team in Embedded Systems, Engineering, Automation, Signal, Telecommunications and
Intelligent Materials (ISASTM), Polydisciplinary Faculty (FPBM), Sultan Moulay Slimane University (USMS), Beni Mellal, Morocco
ARTICLE INFO
Keywords:
Artificial intelligence electric vehicles
Charging stations
Wireless power transfer
G2V-V2G and V4G technologies
Smart grids
MPC
WIFI
ABSTRACT
The aim of this article is to provide a comprehensive overview of electric vehicles (EVs), covering various
related aspects, and addressing the emerging challenges and future prospects associated with them. Within
this framework, an examination is conducted of the fundamental categories of electric vehicles (EVs) and
the related charging methodologies. Given that EVs are anticipated to play a pivotal role in upcoming smart
electrical grids (SEG), deliberations also extend to the intricacies of grid integration, along with explorations
into advanced charging methodologies such as wireless power transfer and communication between station
and center with wireless (WIFI, WIMAX, 5G). This article also examines the current state of EV battery (EVB)
chargers in terms of converter configurations, operational modes, and power regulation strategies for electric
vehicles. EVB chargers are categorized according to their power capacities and the direction of power flow.
Based on power ratings, these chargers are classified into Level 1, Level 2, and Level 3. Certain emerging
charging technologies that have the potential to significantly influence the future of energy storage in the realm
of transportation electrification have been discussed. Regarding the future of EV station chargers focused on
DC fast charging stations, this paper conducts an examination of the design and assessment of various AC/DC
converter topologies in the current context, as well as future strategies for integrating them into DC fast-
charging infrastructures. With this aim, the fundamental characteristics and prerequisites for vehicle-to-grid
(V2G) communications, and prospects for future advancements and electrification scenarios are also introduced
and examined. Compensation reactive power is presented also as V4G (vehicle-for-grid) and some technologies
are used to compensate the grid. Ultimately, the Model Predictive Control (MPC) algorithm has been elaborated
upon using various approaches to provide a deeper understanding of its application in fast chargers through
the utilization of artificial intelligence techniques.
1. Introduction
The persistent use of fossil fuels has worsened numerous environ-
mental issues, such as air pollution and global warming, particularly in
recent decades. Moreover, the global economy has been greatly affected
by the electricity crisis (Sthel et al.,2013). In recent years, endeavors
have been made to minimize automobile pollution, considering that
vehicles consume the bulk of globally utilized fossil fuels. Due to their
usage of electricity generated from renewable energy sources, vehicle
electrification technologies, such as electric cars (EVs) and hybrid
electric vehicles (HEVs), are a viable option for achieving this (Yong
et al.,2015;Un-Noor et al.,2017). However, as passive components
are a new type of cargo, EVs pose a significant technological barrier for
power systems. Consequently, a large number of electric vehicles might
significantly load the grid and have a negative impact on how smoothly
it operates (Lopes et al.,2011;Monteiro et al.,2018). Broadly speaking,
∗Corresponding author.
E-mail address: HAKAM.YOUNESS.fpb21@usms.ac.ma (Y. Hakam).
electric vehicles (EVs) are divided into three primary classifications
based on how and where electricity is generated and supplied (Chau
et al.,2017). Vehicles dependent on a continuous external power
source, like an overhead power line, face a notable limitation: they
are constrained to specific routes to ensure an uninterrupted supply of
external energy needed for their operation. Vehicles that operate by
storing electricity from an external source use either batteries or super-
capacitors to conserve energy. Vehicles internally generate electricity
to meet their needs fall into this category. This includes electric hybrid
cars that utilize thermal motors either in series or parallel with electric
motors, along with EVs featuring fuel cells. Another classification of
EVs is determined by their energy source (Singh et al.,2019). In this
context, two primary categories come into play: battery electric cars
(BEV) and hybrid electric vehicles (HEV). BEVs, often referred to as
‘‘green vehicles’’, ‘‘clean vehicles’’, or ‘‘eco-friendly vehicles’’, produce
https://doi.org/10.1016/j.egyr.2024.04.002
Received 15 October 2023; Received in revised form 30 March 2024; Accepted 1 April 2024
Energy Reports 11 (2024) 4102–4114
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Y. Hakam et al.
Nomenclature
𝐸𝑉 𝑠 Electric vehicles
𝐻𝐸 𝑉 𝑠 Hybrid electric vehicles
𝐵𝐸𝑉 Battery electric vehicle
𝑉2𝐺Vehicle-to-grid
𝐺2𝑉Grid-to-vehicle
𝑉4𝐺Vehicle-for-grid
𝑉2𝐻Vehicle-to-home
𝑉2𝑋Vehicle-to-everything’s
𝑃 𝐹 𝐶 Power factor correction
𝑃 𝐼𝐷 Proportional–integral–derivative
𝑀𝑃 𝐶 Model predictive controller
𝑆𝑅 Swiss-rectifier
𝑀𝑅 Matrix Rectifier
𝑉 𝑅 Vienna-rectifier
𝐷𝑃 𝐶 Direct power control
𝐹 𝐶𝑆 −𝑀 𝑃 𝐶 Finite-control-set MPC
𝐹 𝐿𝐶 Fuzzy logic controller
𝐷𝑇 𝐶 Direct torque control
𝑆𝑀 𝐶 Sliding mode control
𝑊 𝑖𝑀𝐴𝑋 Wireless metropolitan area networks
𝑍𝑖𝑔 𝐵𝑒𝑒 Wireless personal area networks
𝑊 𝑖𝐹 𝑖 − 802.11𝑛Wireless local area networks
𝐼𝑊 −𝑊 𝐶 𝑆 In-Wheel Wireless Charging Systems
𝑊 𝐶𝑆 𝐸𝑉 Wireless charging systems for electric vehi-
cles
𝑆𝐸 𝐺𝑠 Smart electrical grids
𝐸𝑀 𝐼 Electromagnetic Induction
𝑆𝑉 𝑃 𝑊 𝑀 Space voltage vector pulse width modula-
tion
𝑆𝑃 𝑊 𝑀 Sinusoidal Pulse Width Modulation
zero emissions due to their reliance on battery power as an energy
source. They are equipped with larger storage batteries compared to
HEVs, enabling them to achieve longer travel distances. However, the
limited travel range of BEVs poses a significant drawback, as recharging
the battery often requires connection to an external power supply.
An HEV is a vehicle that combines two or more distinct technologies
to facilitate its motion. Typically, these technologies encompass the
conventional internal combustion engine alongside environmentally-
conscious technology, often in the form of an electric motor. However,
the electric motor functions as an auxiliary power source for instances
when the HEV necessitates additional power. Section 1provides a more
comprehensive exploration of HEVs. The development and practical
implementation of efficient charging systems, ensuring swift and de-
pendable EV charging to enhance vehicle range, pose a challenging
area of research (I.E.Agency,2016). Introducing electric vehicles (EVs)
into the transportation sector appears to be a feasible solution. EVs
have the potential to contribute to the electric grid as a distributed
and decentralized energy source. According to certain assessments, a
significant portion of the time – around ninety-five percent – vehicles
remain parked (Clement-Nyns et al.,2009). Kempton introduced the
concept of vehicle-to-grid (V2G), allowing these vehicles to stay linked
to the grid, prepared to discharge the energy stored within their batter-
ies. In times of need, EV technology can support the grid by providing
additional services, including reducing peak power demand, maintain-
ing spinning reserves, and managing voltage and frequency levels (Tran
and Muttaqi,2017). As we move towards transportation electrification,
it is necessary to replace traditional gas stations with Electric Vehicle
(EV) charging stations conveniently located. Furthermore, it is crucial
to explore various onboard energy storage techniques within electric
vehicles (Singh et al.,2018). In broad terms, charging stations can be
classified into three distinct types. Type I employs the standard 120
VAC (US) and 230 VAC (EU) and is suitable for residential charging.
Type II, tailored for public use, operates with 240 VAC (US) and 400
VAC (EU). On the other hand, Type III finds application in commercial
and municipal scenarios such as petrol refueling stations, and it oper-
ates with a 480 VDC supply (Chakraborty et al.,2019). The substantial
battery expenses, limited battery lifespan, intricate charger designs, and
the scarcity of charging infrastructure pose significant challenges for
EVs (Chan and Chau,1997). The performance of chargers significantly
impacts the effectiveness of the grid-to-vehicle (G2V) drivetrain in
EVs (Mwasilu et al.,2014). Electric vehicle (EV) battery chargers can
either be incorporated within the EV as an on-board charger or installed
externally as an off-board charger (Rajendran et al.,2022). Types of
charging will be discussed in Section 3. From 2010 to 2020, the power
density of the traction inverter has seen advancement, increasing from
10 kW/L to 30 kW/L. With consideration to the DC-link voltage, this
density could potentially escalate to 65 kW/L by 2030, resulting in a
reduction of up to 40% in volume. Over the same period, peak inverter
efficiency improved from 92% in 2010 to 96% in 2020, with a projected
potential to achieve up to 98% by integrating wide bandgap technology
into the drive system. This technological enhancement could lead to
a subsequent augmentation of driving range, possibly by as much as
8% (Mierlo et al.,2017). The traction of EV chargers consists of two
types: unidirectional and bidirectional chargers. The DC–DC converter
has used for all topologies of charger, more info can be found in
Section 5. Lithium batteries reign as the predominant battery tech-
nology in electric vehicles (EVs). Within this category, numerous of
distinct lithium battery types with diverse characteristics are available.
Recent developments, as explained in Section 6(Mierlo et al.,2017),
focus on establishing communication between the grid and EV bat-
teries using wireless charging methods. The conventional method for
charging electric or hybrid vehicles typically entails employing a cable
to transmit electricity from the power source. Nevertheless, inductive
charging technology renders cables unnecessary. The envisioned in-
telligent electric car park possesses the capability to purchase or sell
electricity in the format of active and/or reactive power, denoted as
kWh and/or kVARh, to or from the primary grid, enhancing power
quality. Guided by factors such as the car battery bank’s current charge
status, customer requirements, and grid needs, a centralized control
center formulates decisions and dispatches directives for distinct charg-
ing or discharging modes to individual charging stations. Numerous
algorithms are employed to control the flow of energy for v2g and g2v,
some recent and efficient algorithms are model predictive controllers
and PID controllers (He et al.,2020b) This paper delves into the
current state of affairs concerning EV applications, examining a wide
spectrum of technologies and algorithms that have evolved within
this domain. The subsequent sections of this article are structured as
follows: Types of Electric vehicles (EV) and Hybrid Electric Vehicles
(HEV) are presented in Section 1, the station charger will be discussed
in detail in Section 2, while in Section 3analyzing topology designs for
DC fast-charging converters is provided. The state of art battery used for
EVs is discussed in Section 4. In Section 5, wireless charging methods
are discussed with additional information. PID and MPC controllers are
introduced in Section 6, while in Section 7analyzing impact Megawatt
Charging for Long-Haul Battery-Electric Trucks, finally concluding and
some remarks are summarized in Section 8.
2. Types of electric vehicles EV and HEV
Hybrid Electric Vehicles (HEVs) can be categorized based on their
level of hybridization, which is determined by the ratio obtained by
dividing the power of the electric motor (or motors) by the power of the
internal combustion engine. This gives rise to distinct categories, de-
noted as cases A, B, and C. The manner in which energy converters are
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Y. Hakam et al.
coupled to propel the vehicle is even further divided. Cases D, E, F, G,
and H correspond to these categories in this situation (Chan et al.,2010;
Donateo,2017). The compact electric motors of micro-hybrid vehicles,
with power ranging from 3 to 5 kW at 12 V, can initiate the restart of
the internal combustion engine. These motors are not responsible for
propelling the vehicle itself. As a result, a micro-hybrid gasoline vehicle
can seamlessly shut off its engine when stationary (e.g., at traffic lights)
and promptly restart once the driver accelerates, all without relying on
the starter and often without the driver being aware that the engine
has halted. The vehicle’s electric motor is not designed for the purpose
of propelling the vehicle. In ‘‘mild’’ hybrid vehicles, an electric motor
with a power range of 7 to 15 kW and voltage ranging from 60 to 200
V is responsible for initiating the internal combustion engine’s startup
and providing supplementary propulsion to the vehicle. Additionally,
they benefit from the capability to recuperate kinetic energy during
braking. The level of hybridization for mild hybrids falls within the
range of approximately 10% to 30% (Skouras et al.,2019). Another
type of HEV is fully hybrid, more than 25% of the car’s total power in
this category is carried by the electric motor. The motor’s capacity to
operate the vehicle at low speeds and with light loads is 30–50 kW at
200–600 V. The fundamental hybrid vehicle setup involves a tandem
arrangement of a combustion engine and an electric motor as shown in
Fig. 1. In this vehicle category, solely the propulsion system is linked to
the drive. The motor is energized through either batteries or a generator
operated by the internal combustion engine. When the traction demand
intensifies, the generator supplies power to the electric motor, and
when the load is minimal, it replenishes the batteries The generator and
motor have become distinct components, leading to elevated expenses
and decreased performance owing to the incorporation of additional
standalone systems (Propfe et al.,2012). The prevalent drive system
arrangement in hybrid vehicles is illustrated in Fig. 2 through a parallel
configuration. This type of vehicle features a direct connection of inter-
nal combustion engines and motors to the drive system. The subsequent
examples outline various motion strategies. The vehicle moves exclu-
sively through either the internal combustion engine or the motor when
there is minimal need for traction. When only one of the two engines is
in operation, the other will be disengaged using a clutch mechanism. In
scenarios of heightened demand, both engines collaborate to propel the
vehicle. In PHEV systems, it is common for the engine and generator to
be integrated. PHEVs generally employ a smaller battery and traction
motor compared to other hybrid vehicle types. The batteries in a
PHEV (as depicted in Fig. 3) can be recharged through two distinct
methods: by connecting the vehicle to an external power source, or
through internal recharging using the motor-driven generator. Another
approach involves regenerative braking, akin to conventional HEVs.
External electrical power can originate from multiple sources, such as
the power grid, autonomous or household systems, or even renewable
energy sources. PHEVs generally exhibit a reduced electric range per
recharge when utilizing the battery compared to conventional HEVs.
However, they boast a broader overall range, primarily due to the
assistance provided by the motor-generator system when the batteries
are depleted.
3. Electric vehicle charging station
Presently, electric vehicles (EVs) are garnering increasing attention
among researchers owing to their diminished fuel consumption and
reduced greenhouse emissions. These eco-conscious EVs also exhibit
significantly higher energy efficiency, approximately 60%, compared
to gas-powered vehicles which only achieve around 20% efficiency in
converting energy into vehicle propulsion (Nyns et al.,2010). Dur-
ing the initial stages of electric vehicles (EVs), a notable challenge
revolved around their limited driving range due to battery capacity
constraints. However, thanks to advancements in lithium-ion battery
technology, the range of a fully charged EV has considerably ex-
panded from approximately 60 to 120 miles to a substantial 400
Fig. 1. Schematic of series hybrid electric vehicles.
Fig. 2. Schematic pf parallel hybrid electric vehicles.
Fig. 3. Structure of plug-in hybrid electric vehicle.
to 500 miles https://www.energysage.com/electric-vehicles/101/pros-
and-cons-electriccars/. due to this enhancement, electric vehicles (EVs)
have secured a prominent position in the automobile market and have
gained popularity among driversLeveraging advanced grid-to-vehicle
(G2V), vehicle-to-grid (V2G), vehicle-to-vehicle (V2V), and vehicle-for-
grid (V4G) technologies, electric vehicles (EVs) have the capability to
contribute to grid stability through ancillary services, including load
balancing and reactive power support (Kisacikoglu et al.,2012;Yu
et al.,2014). A primary consideration regarding grid power quality
pertains to voltage fluctuations, which can occur when there is a sudden
connection or disconnection of a substantial load (Clement-Byns et al.,
2010). In order to alleviate the strain on power plants and avoid
the need for extra generator startups, the G2V and V2G technologies
enable the charging of EV batteries at night and their discharge during
the daytime. As a result of this, the technology has the capability
to enhance the quality of electricity rather than impose a burden on
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Fig. 4. Block diagram of a typical on-board plug-in AC charging architecture.
Fig. 5. Block diagram of a typical off-board plug-in DC charging architecture.
Table 1
EV charger power levels.
Level 1 Level 2 Level 3
𝑉 𝑜𝑙𝑡𝑎𝑔𝑒 120 V 208 or 240 V 200 or 450 V
𝑡𝑦𝑝𝑒𝑐𝑢𝑟𝑟𝑒𝑛𝑡 AC AC DC
𝐶ℎ𝑎𝑟𝑔 𝑖𝑛𝑔𝑡𝑖𝑚𝑒 4 to 46 h 1 to 6 h 0.4 to 1 h
𝐶ℎ𝑎𝑟𝑔 𝑖𝑛𝑔𝑡𝑜𝑝𝑜𝑙𝑜𝑔𝑦 On-bord(1-ph) On-bord(1 or 3-ph) Off-bord(3-ph)
the electrical grid. EVs possess the capacity to exchange both active
and reactive power with the grid. Given that the grid consistently
requires a spectrum of reactive power, this operation (V4G) serves
to bolster the grid’s performance by enhancing the power factor and
mitigating voltage fluctuations. The incorporation of electric vehicles
(EVs) facilitates bidirectional power flows, power factor regulation, and
mitigation of voltage fluctuations.
3.1. OFF-board and ON-board charger
There are two overarching categories encompassing all-electric ve-
hicle charging methods: Plug-in Charging Method and Wireless Charg-
ing Method. For plug-in charging, there are two additional subcate-
gories: AC charging and DC charging. The onboard battery charging
system is linked to the AC grid through a connector to facilitate plug-
in AC charging. As per the block diagram shown in Fig. 4, the onboard
battery charging system comprises the onboard rectifier, the power
factor correction stage, and the DC-DC converter/charger (Deng et al.,
2014;Gautam et al.,2013,2012). Fig. 5 depicts the standard structure
of an off-board Plug-in DC charging station. In this arrangement, all
power conversion units are situated outside the electric vehicle. To
ensure requisite galvanic isolation for safety, either a sizeable 60 Hz
isolation transformer positioned between the AC grid and the rectifier
or a high-frequency (HF) isolation transformer at the DC–DC conversion
stage is employed. DC-charged electric vehicles (EVs) demand fewer
Fig. 6. Different working operation located in the PQ axis.
power conversion elements, minimizing the need for components both
within and external to the vehicle. The off-board converters directly
replenish the battery within the electric car Du et al. (2010,2011).
3.2. EV charger topologies
Categorized by their power ratings, there exist three classifications
of EV chargers: Level 1, Level 2, and Level 3, as outlined in Table 1.
Motorists have the option to connect their electric vehicles (EVs) to
readily accessible sockets at their residences or workplaces using on-
board chargers designed for Level 1, commonly referred to as slow
charging. Level 2 charging is the prevailing approach utilized for both
private and public facilities, significantly faster than Level 1 charging.
To accommodate Level 2 charging, a 208 or 240 V outlet is necessary.
Level 3 (DC fast) charging is tailored for commercial usage and typically
involves three-phase offboard solutions.
Categorized by the intended direction of power flow, EV battery
chargers can be classified into four categories: unidirectional on-board
chargers, unidirectional off-board chargers, bi-directional on-board
chargers, and bi-directional off-board chargers (Du et al.,2011). The
operational sites available for EV battery chargers are depicted through
the P-Q coordinate system illustrated in Fig. 6 The active power and
reactive power flowing from the grid to the battery are symbolized by
the positive P axis and the positive Q axis, respectively. The PQ plane
can operate in eight distinct modes, contingent on the transmission
direction. The axes within the PQ frame correspond to the operations
of pure G2V, V2G, inductive V4G, and capacitive V4G, designated
as Modes I through IV, respectively. In these processes, the supply
of active or reactive power occurs between the EVs and the grid
through distinct pathways. The system can also be operated at a unity
power factor. The remaining four quadrants encompass V2G or G2V
operations alongside capacitive or inductive V4G operations. In these
operational phases, electric vehicles (EVs) can engage in the exchange
of both active and reactive power with the grid. Through linking
with or detaching from charging stations and delivering or drawing
reactive power, EV batteries can effectively manage electricity loads
and contribute to improving power quality.
3.3. Unidirectional charger
Illustrated in Figs. 7–11 the unidirectional chargers (Modes I, V,
and VIII) operate along the positive 𝑃-axis of the P-Q coordinate.
In this mode, the active power flow is solely provided by the grid
to the vehicle. Additionally, during the battery charging procedure,
the potential for delivering reactive power exists. Nonetheless, this
will result in the introduction of undesirable low-frequency current
harmonics (Yilmaz and Krein,2013).
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Fig. 7. Interleaved unidirectional charger (Kisacikoglu,2013).
Fig. 8. Symmetrical boost rectifier (Yilmaz and Krein,2013).
Fig. 8 demonstrate a symmetrical boost rectifier is a power elec-
tronic converter that combines a boost converter circuit with a rectifier
stage. It is used in various applications like renewable energy systems,
power supplies, and motor drives. The boost converter stage increases
the input voltage to a higher level, while the rectifier stage rectifies
the boosted voltage to provide a regulated output voltage. Symmetrical
boost rectifiers can operate bidirectionally, allowing both step-up and
step-down voltage conversion. They are controlled by sophisticated
algorithms to regulate output voltage, manage power flow, and en-
sure efficient operation. These rectifiers find applications in renewable
energy systems, electric vehicles, battery charging systems, and grid-
connected power converters, offering a versatile and efficient solution
for power conversion needs (Yilmaz and Krein,2013). while Fig. 9
shown An asymmetrical boost rectifier is a type of power electronic
converter that combines features of a boost converter and a recti-
fier to efficiently convert electrical energy. Unlike symmetrical boost
rectifiers, which allow bidirectional power flow, asymmetrical boost
rectifiers are designed for unidirectional power flow, typically from the
input to the output (Kisacikoglu,2013). They are commonly used in
applications where voltage boosting or conversion is required, such as
renewable energy systems, electric vehicles, battery charging systems,
and grid-connected power converters. The asymmetrical boost rectifier
configuration enables efficient voltage conversion by boosting the input
voltage to a higher level, which is then rectified to provide a regulated
output voltage. This type of rectifier is characterized by its ability to
efficiently step up the voltage while maintaining a unidirectional flow
of power, making it suitable for various industrial and commercial
applications. As a consequence, it is advisable for these chargers to
consistently operate in close proximity to the unity power factor, partic-
ularly in Mode I. Numerous configurations have been explored for both
single-phase and three-phase unidirectional chargers, encompassing
topologies such as half-bridge, full-bridge, and multi-level convert-
ers. In low-power scenarios, the power factor correction (PFC) boost
Fig. 9. Asymmetrical boost rectifier (Yilmaz and Krein,2013).
Fig. 10. Inverter buck-boost PFC rectifier (Yilmaz and Krein,2013).
Fig. 11. Unidirectional multilevel charger (Dusmez and Khaligh,2013).
converter, a conventional topology, is employed (Kisacikoglu,2013).
Taking into account factors like costs, dimensions, and component
strains associated with chargers, various circuit topologies are em-
ployed in different application domains. Examples of these topologies
include the interleaved AC/DC boost converter, inverting or positive
buck/boost power factor correction (PFC) converter, and the multilevel
converter (Yilmaz and Krein,2013;Dusmez and Khaligh,2013), as
illustrated in Fig. 10.Fig. 11 demonstrate a unidirectional multilevel
charger is a sophisticated battery charging system that operates in a
single direction, converting AC power to DC power to charge batteries.
It utilizes multiple stages or levels of voltage regulation to optimize the
charging process. This approach offers advantages such as improved
efficiency, faster charging times, and better adaptability to various bat-
tery types and capacities (Dusmez and Khaligh,2013). Unidirectional
multilevel chargers find applications in electric vehicles, renewable
energy systems, and portable electronics due to their efficiency and
precise control over the charging process.
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Fig. 12. Single phase bidirectional charger (Dusmez and Khaligh,2013).
Fig. 13. Three phase bidirectional charger (Dusmez and Khaligh,2013).
3.4. Bidirectional chargers
In efforts to optimize the utilization of EV batteries, intelligent
chargers leveraging V2G technology have been suggested and exten-
sively investigated. Through the utilization of G2V and V2G technolo-
gies, active power can be exchanged between EV batteries and the grid.
When aiming for a power factor of one, these chargers are meticulously
regulated to operate within the 𝑃-axis of the PQ plane. In addition to
facilitating the transfer of active power in V2G/G2V operations, the
capacitor’s provision of reactive power compensation (either inductive
or capacitive) can enhance the power quality of the utility grid. In the
context of V4G operations, the EV batteries can function as capacitor
banks, working in tandem with static compensatorsBear in mind that
it is not desirable for the battery’s longevity and state of charge (SOC)
to be influenced by reactive power operations (Dusmez and Khaligh,
2013). Nonetheless, the operational cycles of charging and discharging
will lead to a decrease in the lifespan of DC-link capacitors. Figs. 12 and
13 illustrates the standard configurations of (a) single-phase and (b)
three-phase bidirectional battery chargers. The majority of EV chargers
are adaptable for connection to a home or workplace socket, catering
to Level 1 (slow charging) or Level 2 (Yilmaz and Krein,2013).
4. Topology designs for DC fast-charging converters
Onboard EV battery chargers can be integrated within an EV,
whereas off-board chargers can be installed as standalone units. Power
flow between EV batteries and grids can be unidirectional or bidirec-
tional. Unidirectional power flow chargers are employed in grid-to-
vehicle charger applications, whereas bidirectional power flow chargers
are utilized in both grid-to-vehicle and vehicle-to-grid charger applica-
tions (Schrittwieser et al.,2018). Unidirectional chargers can control
the charging of EV batteries from the grid (Kisacikoglu et al.,2015;
Tashakor et al.,2017). This paper’s foundation rests on the examination
of available Level 3/DC fast-charging methods. The strengths and
constraints are also emphasized to enhance comprehension. Numerous
converter topologies are at one’s disposal for the swift charging of
Fig. 14. DC fast-charging station.
Fig. 15. Unidirectional boost converter (Singh et al.,2004).
Fig. 16. Matrix converter (Bak et al.,2015).
Fig. 17. SWISS rectifier (Soeiro et al.,2012).
batteries or ultra-capacitors. Several viable alternatives are illuminated
is presented in this section, they are (see Fig. 14):
4.1. Unidirectional boost converter
In Fig. 15, the unidirectional boost converter is illustrated, serving
its purpose when elevating the output voltage is necessary for loads
demanding a higher voltage (Singh et al.,2004). Rather than employing
a conventional diode bridge rectifier, a boost converter is predomi-
nantly employed to enhance power factor, reduce end harmonics, and
maintain a regulated DC voltage at the output in cases of unforeseen
AC disturbances.
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Fig. 18. Vienna rectifier (Kwon et al.,2018).
4.2. Rectifier SWISS
Fig. 17 portrays the SWISS rectifier, which finds application in
scenarios requiring enhanced efficiency (Soeiro et al.,2012). In com-
parison to conventional rectifiers, the adoption of a SWISS rectifier
signifies a significant improvement in efficiency. Buck-type converters,
unlike boost-type converters, provide an extensive range of output
voltage control while retaining power factor correction (PFC) capability
at the input. This configuration permits instantaneous startup and
dynamic current limiting at the output.
4.3. Matrix rectifier
In Fig. 16, the matrix converter is portrayed, serving its purpose
in the regenerative operation of charging stations, particularly in high-
efficiency vehicle-to-grid applications (Bak et al.,2015). The matrix,
a type of forced commutated converter, employs a series of controlled
bidirectional switches to facilitate high-frequency operations. This con-
verter variant does not require a significant energy storage element or
a DC-link circuit. It is capable of enhancing power factor and reducing
harmonics in the ultimate line current.
4.4. Vienna rectifier
The Vienna rectifier, showcased in Fig. 18, stands as another
renowned power converter chosen for its ability to enhance power
quality. It is the favored choice when aiming for a high power factor
and minimal harmonic distortion. Vienna rectifier exhibits minimal
switching losses due to the low voltage stress on its switches (Zou
et al.,2018;Kwon et al.,2018). With just one active switch per
phase, this converter is easier to manage and gains increased reliability.
Essentially, each time the switch is activated, the diodes transfer the
stored energy from the inductor to the load while the switch is in
its off state. An advantage of employing this topology is the absence
of a neutral point connection (Kedjar et al.,2014). Based on the
comprehensive examination of the various converter topologies, it can
be deduced that employing the Vienna rectifier for the realization of the
charging station is fitting, supported by the subsequent justifications:
•It entails a reduced count of switches per phase.
•It effectively compensates for harmonic contents.
•It demonstrates superior efficiency in comparison to the PWM
rectifier, SWISS rectifier, and matrix converter.
•It exhibits a higher power factor of approximately 0.99, surpass-
ing the PWM rectifier, SWISS rectifier, and matrix converter.
5. Algorithms and strategies for converter in EV charger
5.1. Methods and algorithms for efficient energy
Numerous control algorithms have been devised to enhance the
power factor by mitigating harmonic distortions. Diverse power con-
trol strategies, including the hysteresis current controller (Nguyen-Van
et al.,2018), SPWM controller (Al-Ogaili et al.,2019), and direct power
control (DPC) (Zhang and Qu,2015;Mohammed and Kada,2018),
have been introduced. Direct power control necessitates elevated in-
ductance and a higher sample frequency. The hysteresis controller is
frequently employed, albeit leading to increased switching losses due
to the fluctuating switching frequency, as demonstrated in Callaway
and Hiskens (2011). Initially designed for thermostatically controlled
loads (Callaway,2009), this method is now adapted for plug-in electric
vehicle (PEV) charging to dynamically manage a greater quantity of
chargers. Furthermore, various studies have shown that model predic-
tive control (MPC) diminishes line current harmonics and results in a
smaller mean absolute current reference tracking error when compared
to alternative controllers. In Pontt et al. (2007), the writer detailed a
predictive current control mechanism utilizing a voltage source inverter
with an 8 kHz switching frequency to reduce total harmonic distortion
(THD). Meanwhile, Rivera et al. (2013) investigated the use of model
predictive control for a four-leg converter to analyze the reduction
in THD and switching frequency at lower filter parameter values. As
reported in Young et al. (2014), research indicated that a synchronous
proportional–integral (PI) controller with space vector modulation (PI-
SVM) and a finite-control-set MPC (FCS-MPC) exhibit the ability to
generate waveforms characterized by fewer lower-order harmonics
compared to PI-SVM. The MPC approach is capable of functioning
across various voltage/frequency settings while maintaining a reduced
THD level (Yaramasu et al.,2014;Chen et al.,2017). Nevertheless, the
implementation of MPC is more intricate when contrasted with linear
controllers.
5.2. Methods controlling the power converter
A multitude of control strategies have been explored for regulat-
ing power converters and drives in recent times. Mithat and Metin
applied proportional–integral (PI) controllers for both single-phase on-
board and three-phase off-board bidirectional EV chargers (Kisacikoglu
et al.,2015;Kesler et al.,2014). Two external PI loops are employed
to follow reference active and reactive power directives. In previous
works (Kazmierkowski et al.,2002;Linder,2005), hysteresis and lin-
ear controls with pulse width modulation (PWM) have emerged as
the most well-established approaches. However, with the advent of
swifter and more potent microprocessors, the realm of control methods
has advanced significantly over recent decades. More intricate and
efficient strategies like fuzzy logic control, sliding mode control, and
predictive control have gained prominence. Particularly, fuzzy logic is
apt for scenarios in which the controlled system or certain parame-
ters thereof are not ascertainable. Taking into account the attainment
state, prevailing state, and stability state, the switching behavior of
power converters is incorporated within the framework of sliding mode
control. In addition to these control strategies, alternative approaches
like neural networks and neuro-fuzzy systems have been examined
in existing literature (Cortes et al.,2008a). Amongst diverse control
schemes, the predictive control scheme demonstrates superior perfor-
mance in regulating power converters. Its ability to manage numerous
nonlinear variables and constraints is intuitively comprehensible, and
its execution is notably straightforward (Cortes et al.,2008a). The
predictive control methodology demands a greater number of compu-
tations compared to conventional control systems; nevertheless, these
computations can now be swiftly executed with the aid of fast mi-
croprocessors. In general, the effectiveness of the controller hinges on
the accuracy of the model. The foundational principle of predictive
control revolves around utilizing the system model to anticipate the
forthcoming behavior of the controlled variables. Predictive control can
be categorized into four distinct types: deadbeat control, hysteresis-
based predictive control, trajectory-based predictive control, and the
MPC method. Both continuous and finite control sets may serve as the
foundation for the MPC approach. A modulator is required for the MPC
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Y. Hakam et al.
Fig. 19. Block diagram of conventional DPC (Zhang et al.,2017).
with continuous control set to function, and a fixed switching frequency
can be obtained. Conversely, the finite control set MPC operates inde-
pendently of the modulator. Its switching frequency is adaptable, and
the algorithm features low complexity. Both MPC schemes can directly
incorporate constraints.
5.2.1. Direct control power
Derived from the foundational direct torque control (DTC) approach
utilized in AC motor control, DPC focuses on directly regulating the
immediate active and reactive power of the converter system (Zhi
et al.,2008;Idris and Yatim,2002). This scheme’s fundamental idea
is to choose a control vector from a switching table based on the
discrepancies between the estimated active and reactive power levels
and the predicted values, as well as the angle at which the esti-
mated voltage source vector is pointed (Escobar et al.,2003). DPC
exhibits excellent transient performance, robustness, and simplicity due
to its independence from internal current control loops or a PWM
modulator (Monfared et al.,2009;Zhang et al.,2017). A schematic
representation of the conventional DPC methodology applied in the
AC/DC converter is illustrated in Fig. 19. In this setup, the reactive
power reference (Qref) is consistently set to zero to ensure unity power
factor operation, while the reference value for active power (Pref) is
obtained from a PI controller functioning as a DC voltage regulator.
The calculations for active and reactive power, P and Q, are determined
based on the AC-side voltages and currents, as well as the position of
the power source voltage S, situated within the beta. 𝑎𝑙𝑝ℎ𝑎.𝛽 plane’s
12 sectors. The deviations between the observed and anticipated values
of active and reactive power, labeled as dP and dQ, are created using
two hysteresis comparators with fixed bandwidth. Subsequently, based
on these tracking errors (dP and dQ) and the angular position of the
estimated voltage source vector, the switching states for the converter
can be chosen from a switching table during each sampling period.
However, this DPC approach encounters two main challenges. The first
pertains to the sampling frequency, system parameters, reference values
for active and reactive power, and converter switching states which
collectively influence the variable switching frequency. This variability
in switching frequency can lead to the development of a wide harmonic
spectrum in the AC line currents. Yet another obstacle lies in the
necessity to achieve impeccable tracking of time-varying signals, which
mandates the utilization of high sampling frequencies. This renders
the control system highly susceptible to current ripples. Consequently,
the presence of variable switching frequency, substantial power fluc-
tuations, and elevated switching frequencies collectively impede the
practical implementation of this control methodology.
5.2.2. Sliding mode direct power control
Sliding mode control (SMC) is recognized for its remarkable dy-
namic responsiveness and robustness in the face of parameter variations
and disturbances, making it a highly effective strategy for ensuring
system resilience (Repecho et al.,2018). It is a nonlinear control
approach that utilizes a predefined sliding surface as a reference hyper-
plane (Young et al.,1999). A control law is implemented to guide the
trajectories of the controlled system’s state variables onto this sliding
Fig. 20. Block diagram of SMC (Repecho et al.,2018).
surface or towards the desired equilibrium within a finite period (Tan
et al.,2008). Even in the presence of parameter variations or changes in
the load, the controller remains effective with the updated system and
new demands, thanks to the fact that the sliding surface and control
law are grounded in the system model. Fig. 20 demonstrates the appli-
cation of the AC/DC conversion sliding mode control (SMC) technique.
This SMC approach maintains the DC-side voltage by minimizing the
difference between the measured and reference values, denoted as Vdc
and Vdcref. The SMC controller has the capability to generate the active
power Pref reference value. The two errors generated by the hysteresis
comparators are then forwarded to the switching table, where they are
compared with the estimated active and reactive power values. The
selection of an optimal vector will determine the switching states for
the upcoming sample time period. Through the utilization of Lyapunov
stability analysis, it becomes feasible to deduce the stability criteria for
the sliding mode.
5.2.3. Predictive model direct power control
The core idea behind MPC is to create a predictive system model
that can foretell how system variables will behave over an N-step
time horizon (Hu et al.,2013;Tarisciotti et al.,2014). The predictive
model of the system can be represented using a discrete-time state-
space model. The state-space model is employed to forecast all potential
control variables. According to its control objectives, a cost function g
is used to show the discrepancy between the observed and predicted
values of the control variables (Rodriguez et al.,2013;Vargas et al.,
2007). The objective of MPC is to select an optimal switching state
that is closest to the reference value for the upcoming sample. The goal
of MPC is to select the most suitable switching state that is nearest to
the reference value for the upcoming sample period (Ts). This chosen
switching state is aimed at minimizing the cost function g. The block
diagram representation of the MPC system employed in an AC/DC
converter for a single-step prediction can be seen in Fig. 21 (Cortes
et al.,2012). The objective of this system is to control both active and
reactive power. Therefore, the reference and measured values of active
and reactive powers are used in the cost function to determine both a
DC voltage vector and a switching state. Therefore, the specified and
measured active and reactive powers undergo processing within the
cost function, leading to the selection of a DC voltage vector and a
corresponding switching state. Employing space voltage vector pulse
width modulation (SVPWM), the converter’s output voltage, Vdc, can
be managed using eight vectors within the two-phase stationary 𝑎𝑙𝑝ℎ𝑎.𝛽
coordinate system, aligning with the eight available switching states.
Derived from the state-space model, these voltage vectors determine
eight current vectors. Consequently, eight sets of active and reactive
power vectors can be generated and integrated into the cost function,
yielding eight distinct scenarios (Cortes et al.,2008b). From these
various cost function values, the one with the lowest value is chosen
for the subsequent sampling interval. Upon selecting the minimum cost
function, both an active power and a reactive power can be ascertained,
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Y. Hakam et al.
Fig. 21. Block diagram of MPC.
Fig. 22. Block diagram of MPSMC.
alongside the corresponding current vector. With the relevant voltage
vector and the selected current vector, a suitable switching state can
be determined. This ultimately enables the adjustment of active and
reactive powers to align with their respective reference levels.
5.2.4. Predictive sliding mode control based on a model
As illustrated in Fig. 21, the conventional model predictive control
method generates the active power reference through a proportional–
integral (PI) controller. Nonetheless, the conventional approach of
this model predictive method leads to notable overshooting or un-
dershooting, prolonged settling periods, and considerable steady-state
inaccuracies when subjected to disturbances. The manual tuning of
PI coefficients to achieve an optimal set is challenging. Furthermore,
maintaining a fixed pair of PI coefficients to accommodate changing
system parameters and requirements proves impractical. To address
these shortcomings, a sliding mode controller is introduced to replace
the PI controller in He et al. (2020a). By designing the control law
and controller according to the system model, the model predictive
sliding mode control (MPSMC) technique can mitigate the impacts of
unforeseen disturbances, like changes in output voltage demand and
load resistance. A control block illustrating the model predictive sliding
mode control scheme is depicted in Fig. 22.
Fig. 23. Main components of wireless charging system.
6. Wireless EV chargers
Because of its straightforward nature, wireless power transfer, an
emerging technology, is currently finding application in EV chargers
for transmitting power over significant air gaps (Lee and Han,2015).
Typically, a wireless charging system comprises the elements illustrated
in Fig. 23 a utility interface, an off-board power converter with a
controller, off-board coils, on-board power electronics, and a commu-
nication interface that links the roadside and vehicle-side radios. The
off-board power converter consists of an AC/DC power factor correction
converter and a high-frequency DC/AC converter. The wireless charger
uses a magnetic field to transmit electricity rather than a physical con-
nection or a typical transformer (Li et al.,2016). Wireless EV chargers
encounter various challenges, such as safety considerations, achieving
efficient power transfer at high power levels, managing increasing
power demands, and accommodating misalignment.
6.1. Communication techniques between Electric Vehicles (EVs) and the
central controller
For the transfer of control data and signals in the smart micro-
grid, wireless telecommunications have become increasingly popular
recently. Wireless local area networks (WiFi-802.11n), wireless per-
sonal area networks (ZigBee), and wireless metropolitan area networks
(WiMAX) are the three most common technologies now in use (Gungor
et al.,2010).
6.1.1. WIFI
Wi-Fi technology is founded on IEEE 802.11 standards and has been
utilized in various network types such as 802.11b, 802.11a, 802.11g,
and 802.11n. The initial 802.11b network achieved data transfer rates
of up to 11 megabits per second (Mbps) (Sidhu et al.,2007). Sub-
sequently, 802.11a and 802.11g followed, offering maximum speeds
of 54 Mbps with throughput rates around 25 Mbps. Driven by the
demands of consumers and businesses for increased bandwidth.
6.1.2. ZigBee
ZigBee is a contemporary technology that enhances wireless per-
sonal area networks (WPANs). It represents a set of high-level com-
munication protocols designed to establish personal area networks
using small, energy-efficient digital radios based on the IEEE 802.15.4
standard (Sidhu et al.,2007;Fadlullah et al.,2011).
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Y. Hakam et al.
Fig. 24. The S-WEVC system.
6.1.3. WiMAX
In June 2004, the IEEE ratified the 802.16 standard, also known
as WiMAX (Intel Corporation,2003). It can be used for WiFi-style
wireless networking. Higher data rates over greater distances and ef-
fective capacity utilization are also possible with WiMAX. Additionally,
interference can be minimized.
6.2. Wireless charging
The conventional approach to charging electric or hybrid vehicles
involves using a cable to transmit electricity from the power source.
However, inductive charging technology eliminates the necessity for ca-
bles by utilizing an electromagnetic field to transfer energy between the
source and the recipient. Wireless inductive charging can be classified
into two types: static charging, where the vehicle remains stationary
over the charger to initiate battery charging, and dynamic charging,
where the vehicle charges while in motion on the road (Magudeswaran
et al.,2019;Intel Corporation,2003).
6.2.1. Static wireless charging system
A stationary wireless Electric Vehicle Charging System (EVCS), as
shown in Fig. 24, operates based on principles similar to those of a
transformer, facilitating the transfer of energy from a primary coil to a
secondary coil (Magudeswaran et al.,2019). In the initial stages, AC
voltage is transformed into DC through an AC/DC rectifier. Follow-
ing this, a high-frequency DC/AC converter supplies high-frequency
current to the primary coil, which is positioned along the roadway.
In this arrangement, the current in the transmitting coil generates an
alternating magnetic field, leading to the induction of an alternating
voltage in the receiving coil. The receiver’s secondary coil, which
is mounted underneath the front, back, or center of the vehicle, is
crucially constructed to prevent major losses from wear and tear,
inappropriate handling, and the inability to identify foreign objects. A
resonant capacitor is incorporated in the secondary coil to enhance the
power transfer capability of the system. The alternating voltage in the
secondary coil is then transformed into direct current using an AC/DC
converter, facilitating the charging of the vehicle’s battery. Wireless
charging systems offer advantages such as simplicity, reliability, user
safety (protection against electric shock), and user-friendliness, poten-
tially replacing the traditional plug-in electric vehicle (PEV) charging
cables.
6.2.2. Wireless Charging Systems integrated within wheels
Integrated Wireless Charging Systems within Wheels, the efficiency
of wireless charging is greatly influenced by the gap between the
Fig. 25. In-wheel wireless charging.
transmitting and receiving components. The development of In-Wheel
Wireless Charging Systems (IW-WCS) offers a solution to optimize
charging performance for both stationary and dynamic scenarios. In-
ductive Charging (depicted in Fig. 25) enables the vehicle to be charged
whether it is stationary or in motion (Bouanou et al.,2023). Just
like other wireless charging systems, the primary coils are positioned
beneath the pavement’s surface. Electronic circuits then transform the
supplied current into a high-frequency (HF) AC signal operating at
100 kHz. The setup involves a primary coil circuit connected to primary
windings. On the tire structure, secondary coils are installed. This
configuration results in a reduced air gap between the source and
receiver coils compared to existing static or dynamic wireless charging
systems for electric vehicles (WCSEV). The precise internal positioning
of the receiver coils is illustrated in the figure above. This arrangement
offers several benefits (Panchal et al.,2018).
7. Megawatt charging: Influence on battery dimensions and cell
specifications for long-Haul battery-electric trucks
The recently introduced Megawatt Charging System (MCS) standard
is set to facilitate the recharging of a significant portion of the battery
in Battery Electric Trucks (BETs) during mandatory rest periods within
the European Union. Our study delves into the implications of this
novel standard on both the necessary battery capacity and the specific
cell characteristics essential to achieve operational equivalence with
a diesel truck (DT) across various operational strategies. According
to EU regulations for truck driving, a single-stop operating approach
is permitted, allowing trucks to be charged during the mandatory
45-min break following 4.5 h of driving (Schneider et al.,2023). In
2019, commercial vehicles contributed to 38% of transport emissions
in the EU (European Commission,2021). To address this environmental
impact and meet climate objectives, the EU has established targets
for reducing emissions in the commercial vehicle sector 15% by 2025
and 30% by 2030 compared to 2019 (European Union,2019). Nu-
merous studies suggest that Battery Electric Trucks (BETs) will play
a significant role in the future zero-emission transport fleet (Booto
et al.,2021;Wolff et al.,2021). To facilitate the transition to BETs for
truck operators, it is essential that BETs are seamlessly integrated into
operators’ logistics processes and offer Total Cost of Ownership (TCO)
advantages. In addition to exploring cable-based charging, research
is underway to examine battery swapping and catenary systems as
energy supply technologies for Battery Electric Trucks (BET) (Wu et al.,
2021;Speth and Funke,2021). Progress is being made in all three
technologies within both the research and industrial sectors. However,
as European manufacturers primarily prioritize establishing a robust
cable-based charging network (milence,2022) and incorporating the
Megawatt Charging System (MCS) into their future products (CharIN,
Energy Reports 11 (2024) 4102–4114
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Y. Hakam et al.
2022), this article concentrates on cable-based charging. In this context,
a pivotal facilitator for the technology is the aforementioned Megawatt
Charging System (MCS), designed with specifications extending up to
3000 A and 1250 V. Consequently, this enables a charging power
of up to 3.75 MW at a single charging point. Although this stan-
dard is presently undergoing standardization, numerous companies
and institutions have declared substantial investments and a political
commitment to incorporating the standard at numerous rest areas
in the coming years (milence,2022;CharIN,2022;Federal Ministry
for Digital and Transport,2023). Anticipated to meet this level of
charging power, the intention is to utilize driving breaks mandated
by EU regulation 561/2006 (EU Parlament,2006) for on-the-go charg-
ing, thereby significantly reducing the required battery size to fulfill
the driving task (Nykvist and Olsson,2021). Additional research has
delved into investigating how cell properties impact the Total Cost
of Ownership (TCO) for Battery Electric Trucks (BET). In a study
by Mauler et al. (2022), various cell chemistries in BETs were com-
pared to fuel cell trucks, taking into account factors such as required
range and whether the transport is constrained by volume or weight.
The findings revealed that lithium iron phosphate (LiFePO4 or LFP)
cells, characterized by lower gravimetric energy density and higher
cycling stability, offer cost advantages in volume-constrained applica-
tions exceeding 800 km. Conversely, cells incorporating nickel cobalt
manganese oxide (Li(NixCoyMnz)O2 or NMC) cathode prove beneficial
in weight-constrained transport within the range of 300 km to 600
km due to their higher energy density. Depcik et al. (2019) explored
the viability of different lithium-ion and advanced beyond lithium-ion
batteries, assessing their attributes for a 500 km use case. The study
indicates that the specified use case is achievable with existing lithium-
ion technologies. However, the distinct properties dependent on cell
chemistry introduce significant variability in the characteristics of the
vehicles.
8. Conclusion
The progression of electrification, aimed at harnessing renewable
energy sources, is underway. The ultimate goal is the seamless inte-
gration of electric vehicles (EVs) into smart electrical grids (SEGs).
This shift from traditional vehicles on one end to fully electric-powered
ones, on the other, facilitated by exchanging electricity with the grid,
inevitably requires intermediate stages. Among these stages, hybrid
electric vehicles (HEVs) play a crucial role in showcasing the advan-
tages of this emerging technology to consumers, ensuring a seamless
transition towards widespread adoption of electric propulsion. This arti-
cle review is dedicated to exploring various systems for electric vehicles
(EVs), encompassing plug-in electric vehicles (PEVs) and hybrid electric
vehicles (HEVs).
•The analysis focuses on dissecting aspects of the EV station
charger.
•Diverse topologies covered: inverters, rectifiers, and DC–DC con-
verters. Scrutiny is given to multiple charging levels: Level 1,
Level 2, and Level 3.
•The efficacy of the Model Predictive Control (MPC) algorithm’s
efficacy in charging.
•Discussion on communication protocols: WIFI, WiMAX, and 5G
connectivity.
•A Comprehensive exploration of wireless charging methods is also
included.
•Electromagnetic Induction (EMI) is identified as the most effective
power transfer technique.
CRediT authorship contribution statement
Youness Hakam: Writing – original draft, Validation, Resources,
Conceptualization. Ahmed Gaga: Writing – review & editing, Visual-
ization, Supervision. Benachir Elhadadi: Supervision.
Declaration of competing interest
The authors declare that they have no known competing finan-
cial interests or personal relationships that could have appeared to
influence the work reported in this paper.
Data availability
Data will be made available on request.
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