**1. Introduction**

To acquire a proper pace to meet the increasing demands of sustainable transportation one may come across many technical hurdles that currently exist in the area of electric vehicles and their electrification mobility plan [1]. As per the literature survey [2–4], it has been observed that the price of current electric vehicles, range, and the facilities to charge them are the major concerns in the present market of electric vehicles. With time, these three challenging issues have gone through tremendous evolution. For instance, the price has been decreased by almost 90 percent and it is predicted that it may reduce more in future by 2050. Its range comparatively has been increased from 80–160 km to 320+ km [5–7],

**Citation:** Abro, G.E.M.; Zulkifli, S.A.B.M.; Kumar, K.; El Ouanjli, N.; Asirvadam, V.S.; Mossa, M.A. Comprehensive Review of Recent Advancements in Battery Technology, Propulsion, Power Interfaces, and Vehicle Network Systems for Intelligent Autonomous and Connected Electric Vehicles. *Energies* **2023**, *16*, 2925. https://doi.org/ 10.3390/en16062925

Academic Editors: Ahmed Abu-Siada and Byoung Kuk Lee

Received: 26 February 2023 Revised: 13 March 2023 Accepted: 21 March 2023 Published: 22 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

whereas the charging infrastructures have been observed as still a major concern. These electric vehicles are no doubt environmentally friendly [8,9] and have the great boom of renewable sources in the electrical grid, as witnessed in [10]. This review manuscript will try to address these issues in more detail along with emphasizing the current cutting-edge advancements in this e-mobility [11–13].

Looking at 2020, one may see that the battery's specific energy has been increased from almost 110 Wh/kg to 250 Wh/kg. Hence, looking at this advancement one may predict that it may reach up to 450 Wh/kg by the year of 2030. Moreover, the energy density also increased from 300 Wh/L to 550 Wh/L from 2010 to 2020 (in merely 10 years). Thus, one may also predict for 2030 that it may increase up to 1100 Wh/L. Where the prices of batteries are concerned, there is reduction in the cost as well. The battery price that used to be EUR 1200 per kWh has been reduced to EUR 120 per kWh and will likely to go down to EUR 50 per kWh in the near future. This review paper therefore shares the current state of the battery technology as well [11–13].

Discussing further the traction inverter power density, one may see that it is also increased up to 35 kW/L and likely to be increased up to 60 kW/L in the upcoming 10 years [11]. Researchers have so far incorporated wide band gap strategies to increase the efficiency up to 98% with an increment in driving range by 8%. The method utilized to generate electricity has the biggest impact on how environmentally friendly electric vehicles are. The European Energy Mix estimates that CO2 emissions in 2010 were at 300 CO2 g/kWh. The deployment of sustainable energy sources and the potential retirement of nuclear power plants are expected to reduce CO2 emissions to below 200 g/kWh by 2030, and maybe even lower. The CO2 emissions per vehicle will drop from 66 CO2 g/km in 2010 to under 30 CO2 g/km in 2030 when the consumption and emissions of the electric vehicles used to generate the electricity are taken into account [11–14].

Autonomous vehicles (AVs) are anticipated to be used by 2030. They will probably be electric and shared. Some of the commercial used vehicles have been incorporated with automation level 1, as mentioned by the SAE in 2010. Now, the latest cutting-edge vehicular technologies have reached level 3 already, and some of them have level 4 automation. They have artificial intelligence features already incorporated with advanced communication systems that enable their use for brand new mobility services right now. Such development is also present in this article. In this present era, thousands of things cannot only be sensed but processed and actuated using the Internet of Things feature. This will also enable the smooth collaboration and makes sharing of data easy [14–16]. Such platforms are used in the automotive mobility, automation, as well as in smart cities. These platforms are not only used to identify threats but also used to tackle them [14–20]. While driving one may see that driver has to perform a series of actions, such as accelerating and de-accelerating the vehicle, taking care of directions, and using indicators and changing lanes accordingly [21]. An autonomous vehicle must consider its surroundings in order to operate [22]; the five core processes of perception and planning, along with localization, vehicle control system, and system administration, are needed for this.

Estimating the position of the vehicle is the responsibility of the localization module, while the perception module uses data from several sensors to build a representation of the driving environment. Thus far, the module related to planning is concerned; its main task is to make decisions for maneuvering the EV based on safer localization and mapping. This is all possible because of the perception data only. Moreover, the acceleration, steering, and braking mechanisms all are controlled by the vehicle control system [23]. Thus, taking all factors on the road into account, such as pedestrians, cyclists, other vehicles, etc., the procedure becomes a bit complex. Therefore, the communication system module plays a vital role in the autonomous electric vehicles, which allows the vehicle to take care of such factors while being driven on roads. A frequent name for this type of communication is "vehicle-to-everything" (V2X) communication, which encompasses a number of situations including "vehicle-to-vehicle", "vehicle-to-infrastructure", "vehicle-to-pedestrian", and "vehicle-to-network" (V2N) communication [24,25].

Thus far, it has been observed and studied in the literature [25,26] that two vehicles can communicate with each other, known as vehicle-to-vehicle communication. This enables fewer collisions and enables road departure with nominal speed and acceleration by letting other side vehicles know about each other [27]. Instead, V2I communication allows the car to link to the infrastructure on the side of the road to spread information widely [28]. Among the advanced services, one may find all relevant information related to safe distances from surrounding cars, speed limits, safety, roadblocks, and accidental warnings, and it also helps in assisting lane tracking as well [29]. In order to reduce accidents, the term "V2P" refers to the idea of information being exchanged between a vehicle and a pedestrian utilizing sensors and intelligent technology [30–32]. The server that provides centralized control and data on traffic, roads, and services is connected by V2N, which connects car user equipment [33]. As a result, the deployment of V2X communications in conjunction with already existing vehicle-sensing capabilities serves as the basis for complex applications intended at enhancing vehicle traffic, passenger infotainment, manufacturer services, and road safety [34,35].

If such systems are to be successful when implemented in a real-life scenario, they will ultimately depend on the data gathered from actual contact [36]. For instance, machine vision makes use of image processing to keep an eye on the back cars [37] and trajectory analysis of the vehicles in particular jurisdiction [38]. The best control parameters for maximizing fuel efficiency and saving fuel are also determined using historical data [39]. The chance of drunk or sleepy driving is decreased by using data gathered by in-car sensors to examine driver behavior even when the vehicle is not fully autonomous [40].

There is literature that examines V2X communication and focuses on the connectivity and security of networks [41–45]. There have also been reviews that concentrate on various aspects of the autonomous vehicle. The state of the art for connected automobiles was outlined by Siegel et al. [40] starting with the obstacles, applications, and requirements for vehicle data. It was endorsed in [46] that the communication between transport infrastructures with cooperative traffic management solves half of the problems. They focus on non-signalized junctions in their study while also including approaches for signalized intersections. The detailed review on autonomous overtaking was published in [47]. The authors demonstrated that the dynamics of vehicles and restrictions associated with the environment, as well as proper understanding of the environment and nearby obstructions, are the two key components of high-speed overtaking. Bresson et al. [48] conducted an assessment on localization methods for autonomous cars equipped with on-board sensor-based systems along with the combination of a communication network, either V2V or V2I, or in some of the cases both are equipped.

## *Development of Vehicular Networks and Cloud Options*

Furthermore, one may see several research contributions revolving around cloud computing [49–58]. In these research manuscripts, authors have investigated the vehicular computing based on cloud things and associated its extension to mobile-based cloud computing and vehicular networks. In addition to this, one may find additional information related to privacy, security topics, and concern areas such as cloud applications and their formation along with the communication system design. The difficulties of vehicle cloud networks were discussed in [50,51]. Last but not least, one may see similar discussions on vehicular cloud options, including traffic models, services, and applications that can make vehicular clouds possible in a more dynamic setting [52,53]. Reviews written by various authors have concentrated on a certain topic. Although review paper [40] focused on a more general topic, network connectivity was highlighted. The application had very few details. However, the researcher in [40] only highlighted applications that may use gathered data to check drivers, hence lowering the danger of sluggish drinking, as an example of driver monitoring. As per our best efforts on studying the literature, one may be unable to find any study related to the cutting-edge trends in autonomous vehicular technology. Hence, the aim to include this in our review manuscript is to comment whether the abovestated jobs will be performed by the modern autonomous vehicular technology or not. Fuzzy, modern predictive control, and a number of other techniques are used to enhance fuel efficiency and energy consumption without sacrificing the vehicle's performance. Some of these provide information on the EMS's real-time development process and its calibration parameters, which are utilized to improve the vehicle output characteristics. These parameters include SOC, vehicle speed, power-split, etc. The primary goal of this type of research is to investigate a comprehensive strategy for creating the control architecture of an EMS using multiple control techniques. Along with a brief suggestion and debate regarding the improvement of future EMS research, constraints and difficulties relating to EMS breakthroughs are also suitably emphasized. The significance and potential effects of real-time EMSs with different control systems were finally revealed by an interpretative analysis [39]. For the transportation of the future, which is anticipated to be sustainable in terms of energy generation, consumption, and vehicle emissions, these methods are all put forth. Vehicle electrification, autonomy, and implementation all heavily rely on embedded intelligent systems. Despite the fact that electric vehicle technology is anticipated to dominate the automotive powertrain design in the next decades, a number of obstacles currently prevent their widespread adoption in the automotive industry. These obstacles can generally be divided into four categories: consumer behavior, charging infrastructure, car performance, and governmental backing. Hence, a thorough understanding of these obstacles is a matter of concern. Based on the importance of each barrier to be found and removed, this article studies them and deduces the relative order of their removal [40].

This paper starts with information about the digital-twin-based vehicle propulsion system (DTVPS) and its revolutionary benefits associated with the wide band gap (WBG) based semiconductor trend utilized in power converters. Later, one may read about the rapid charger technology in detail with respect to vehicle-to-grid (V2G) and vehicle-todevice (V2D) communication systems [59,60]. In addition to this, one may see the overall investigation provided by these modern strategies that make modern autonomous cars more powerful. At the same time, there is a recommendation of resolving the issues as stated in this manuscript. Thus, the main objective of this research article is to propose an overall picture of this topic though comprehensive literature work which includes related areas but no discussion on algorithms at this moment.

#### **2. Future Electric Vehicle Propulsion Systems**

In terms of the concept related to electric vehicle propulsion systems, one may understand it in an easy way, as it requires a power converter, a battery, an electric motor, and, last but certainly not least, a fixed transmission. Moreover, there is no need for a gearbox, and it is also free from clutch and oil filters. This cuts down the costs as well as improves the driving comfort [61–64]. One may find the information associated with the upcoming market trends with EV propulsion in this section and will be able to draw the new directions for research as well.

#### *2.1. Development of Digital Twins for EVs and Their Perks*

For many years, automotive researchers and engineers have created analytical and simulation models of the individual parts of EVs as well as complete EVs. With time, these models have advanced and become more precise. With the advent of sensor technologies and the powerful IoT-like feature, all offline models have been turned into digital models that provide liberty of monitoring, rescheduling maintenance, predictive maintenance, and fault endurance and recognition for their lifetime. This results in reducing the costs over the intermediate steps during manufacturing, such as system design verification and validation. These are the reasons that digital twin has been initiated based on the advanced strategies such as AI, IoT, and cloud computing [65,66].

The entire idea about digital twin is illustrated in Figure 1, where one may see an electric vehicle containing all essential components, such as a power converter, battery, and then a suitable number of sensors equipped with a motor. The representational model of

the simulation platform is housed in the virtual environment. Thus, using a multi-physics framework, one of the highly accurate models has been developed. The exchange of information and data links the physical and digital worlds. The vehicle designer can develop a virtual process that runs concurrently with the real one and functions as a source that helps in analyzing the model in terms of dynamic and static perspectives.

**Figure 1.** The creation of a digital twin implementation concept.

The EV's digital twin model and tool can provide the following advantages:


Additionally, maintenance protocols and schedules can be created utilizing the data collected from the digital twins of the cars to ensure that the parts are available before they are anticipated to fail in the EV and reduce inventory stocks. The use of the digital twin in control design, designing powertrain, and the dependability of innovative new powertrains is also one of the major themes of the future. This shares three significant domains, such as the digital-twin-based reliability, its design itself, and digital-twin-based control design. These areas are all crucial for creating future vehicle generations that are more dependable and cost effective.

#### *2.2. Power Electronic Interfaces*

Power electronic converters are no doubt important components of any electric vehicle propulsion [11]. Numerous studies have been undertaken in the area of semiconductor -based materials designed as switches for these power converters. These switches are currently proposed based on silicon (Si) materials or silicon carbide (SiC). A few of them use gallium nitride (GaN), as referred to in [67–70]. The only limitation or constraint with such switches is their switching frequency. As per the user requirement, it is seen that the silicon-based IGBT traction inverter designs restrict the switching frequency [71]. These wide band gap materials need one- or two-electron volt energy to transfer their electron to the valence band in order to execute the conduction [67–73]. Such properties are illustrated in Figure 2.

**Figure 2.** Comparison between silicon (Si), silicon carbide (SiC), and gallium nitride (GaN) [73].

For Si-based OBCs, the switching frequency for MOSFET-based on-board chargers (OBCs) must be less than 100 kHz [72]. The WBG semiconductors, in contrast to typical Si semiconductors, have intriguing characteristics and advanced material features, such as the capacity to function at higher voltages and with less leakage current, as well as greater switching frequencies and thermal conductivity. Thus, for low-voltage applications, the high-frequency-based WBG semiconductor provides good efficiency along with better power density. This results as a reduction in the overall weight of the converter and efficiency of the electric powertrain. Moreover, these high frequencies that are in between 40 kHz–100 kHz for active front-end inverters and 200 kHz to 500 kHz for OBC systems will allow to even operate on high temperature readings as well. It has been observed that there is much less focus dedicated to the thermal control of GaN-based semiconductor devices. Thus, precise models for GaN-based power electronic converters are required so that one may suggest the outcome based on their parametric as well as non-parametric representations.

Additionally, for power electronic converters, the most failure-prone devices are the semiconductor modules. This is because of their high thermal stress property. Many of these failures are time-dependent dielectric breakdowns [74]. WBG-based power converters are most reliable because of their higher activation and are currently preferable due to their cost-effective packaging devices. These reliability operations have so far not been discussed in previous research contributions. Although there are some research manuscripts that may share the reliability analysis of silicon- and silicon-carbide-based converters, one may find very little research on GaN-based power converters. These GaN devices in the EV power industry enable higher range efficiency, but still one of the key constraints in this area to tackle is the range of voltages. Regarding the predictive maintenance and reliability, no detailed stress study is available. Therefore, in accordance with these WBG technologies, one may see them being integrated with electric motors as well as with the battery systems.
