Ai-optimized autonomous propane-powered ev charging fleet for in-motion services

Abstract

A fleet-based mobile electric vehicle (EV) charging system is disclosed, comprising self-driving trucks with on-board generators powered by eco-friendly propane. The technology mitigates anticipated regulatory constraints on nighttime grid charging during periods when solar farms are inactive. Autonomous navigational capabilities empower the trucks to locate and rendezvous with EVs requiring power, seamlessly delivering charge in motion. Such dynamic charging sidesteps the need for traditional stationary infrastructure and conforms to evolving regulations by offering a versatile, on-demand alternative. Propane's clean combustion underscores this system's environmental advantage over conventional grid reliance, especially during nocturnal hours. Charge initiation is automated through secure wireless communication protocols upon the truck's connection with an EV. Route optimization and scheduling are intelligently managed using artificial intelligence, enhancing both the efficiency and availability of the mobile charging service. The charging trucks provide both safety and reliability when delivering energy to EVs in transit.

Description

AI-OPTIMIZED AUTONOMOUS PROPANE-POWERED EV CHARGING FLEET FOR IN-MOTION SERVICESCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to or benefit of United States provisional patent application No. 63 / 610,735, filed December 15, 2023, which is incorporated herein by reference in its entirety.TECHNICAL FIELD

[0002] The present disclosure relates to electric vehicle (EV) charging systems. More specifically, it relates to autonomous mobile charging solutions utilizing environmentally friendly power sources.BACKGROUND

[0003] The electrification of the transportation sector has led to a proliferation of electric vehicles (EVs) on the roadways, necessitating a robust and accessible charging infrastructure. The current landscape of EV charging technology predominantly relies on fixed charging stations, similar to traditional fuel stations, which serve as the primary hubs where EV owners replenish their vehicle's batteries.

[0004] However, these fixed stations have several limitations. They require significant capital investments for their installation and maintenance, which can result in an uneven geographic distribution, with stations often concentrated in urban and suburban areas. This leads to a disparity in charging accessibility and capacity, particularly in rural or underpopulated areas. The result is a demand for EV charging that far outstrips the supply in these locations, forcing EV owners to plan their routes meticulously to avoid being stranded without power.

[0005] The reliance on grid electricity for these charging stations presents additional drawbacks. Most notably, the electrical grid is subject to fluctuations in power supply and demand. As charging stations draw considerable power from the grid, they can contribute to peak load issues, especially during daytime periods when EV owners may prefer to charge their vehicles. Additionally, many grids are still heavily dependent on fossil fuels, which diminishes the environmental advantages of EVs themselves.

[0006] Time-of-use (TOU) regulations have been instated in various regions to mitigate these impacts. These regulations encourage electricity consumption, including EV charging, during off-peak hours — often overnight — when demand is lower and electricity is typically cheaper. While TOU rates can help balance the grid load and offer cost savings to consumers, they also impose restrictions on when EV owners can conveniently charge their vehicles. As a growing number of solar and wind energy sources are integrated into the grid, mismatched supply and demand present further challenges, since these renewable sources cannot always provide power to meet nighttime charging requirements.

[0007] The current EV charging paradigm, therefore, presents a complex interplay of accessibility issues, grid dependency, energy source considerations, and regulatory frameworks. There remains a clear opportunity for innovation in order to overcome these challenges.SUMMARY

[0008] It is an object of the present disclosure to provide systems and methods for charging electric vehicles during their motion. An optimized by an artificial intelligence (Al-optimized) autonomous propanepowered electric vehicle charging fleet for in-motion services is disclosed herein. The electric vehicle as referred to herein may be an electric car, an electric truck, an electric aircraft (a vehicle that is able to fly), including but not limited to, an electric drone (which is an unmanned aerial vehicle), or any other type of vehicle the propulsion of which is powered fully or mostly by electricity. In at least one embodiment, the system and method as described herein may be used to charge electric aircrafts, in such embodiment the charging vehicle is a charging aircraft, which has the same features as described herein for the charging truck, and the electric vehicle is an electric aircraft.

[0009] The system as described herein uses artificial intelligence (Al) for optimization. The system has the autonomous nature of the operation. The system uses the propane power source which adds to the ecological aspect. The system and method as described herein may be used for a fleet of charging tracks, and therefore may be scalable. The system and method as described herein provides charging services while electric vehicles are in motion, allow to provide unique service, and distinguishing the technology as described herein from conventional stationary electric vehicle charging solutions and may allow to comply with grid-use regulations.

[0010] According to one aspect of the disclosed technology, there is provided an autonomous mobile electric vehicle charging system for charging electric vehicles, the system comprising: a fleet of charging trucks autonomous from each other, each charging truck being equipped with an onboard propanepowered generator; an autonomous navigation system configured to guide the charging trucks to the electric vehicles ; a wireless communication interface configured to initiate charging sessions between the charging trucks and the electric vehicles; and an artificial intelligence module configured to optimize routes and scheduling of the charging trucks based on demand and traffic conditions. The propane-powered generator may be also configured to power the charging truck while providing electricity for EV charging. The system may further comprise a charging interface mechanism adapted for establishing a connection with the EVs to provide in-motion charging capabilities. In at least one embodiment, the system is configured to generate adaptive scheduling that allows the charging trucks to deploy pre-emptively based on predicted demand patterns identified through Al analysis. The autonomous navigation system may comprise sensors located on the charging trucks and configured to collect data in real time from anenvironment surrounding the charging trucks. The wireless communication interface may use secure protocols to authenticate the electric vehicles before commencing charging sessions.

[0011] According to another aspect of the disclosed technology, there is provided an autonomous mobile electric vehicle charging truck comprising: a propane fuel storage system; a propane power generation unit connected to the propane fuel storage system; an autonomous navigation control module configured to receive and interpret data from autonomous driving sensors for autonomous vehicle operation; a control and distribution unit configured to regulate electricity flow from a generator to the electric vehicle; an interface mechanism configured to facilitate energy transfer to an EV; and a communication module configured to initiate and to control an automated charging session. The autonomous mobile electric vehicle charging truck may further comprise a safety management module configured to continuously monitor operation of the autonomous mobile electric vehicle charging truck to identify and to respond to a safety issue.

[0012] According to another aspect of the disclosed technology, there is provided a method for charging electric vehicles using an autonomous mobile charging truck, the method comprising: navigating the charging truck to an electric vehicle based on Al-optimized routes; autonomously establishing a charging connection with the electric vehicle; managing and controlling a flow of electricity from a propanepowered generator to the electric vehicle; wirelessly communicating between the electric vehicle and the charging truck to synchronize and control the charging session. In at least one embodiment, the charging truck provides charging services to the electric vehicle while both the charging truck and the electric vehicle are in motion. Al-optimized routes may be generated by an Al routine which is configured to adjust truck routes in real time in response to traffic conditions and demand distribution.

[0013] According to another aspect of the disclosed technology, there is provided a system for providing mobile electric vehicle charging services, wherein the system is configured to use propane as a fuel source for generating electricity required for charging the EVs. In at least one embodiment, the system is configured to generate adaptive scheduling that allows the charging trucks to deploy pre-emptively based on predicted demand patterns identified through Al analysis.

[0014] According to another aspect of the disclosed technology, there is provided a mobile electrical vehicle charging truck configured to interface safely with electric vehicles and provide in-motion charging, wherein the truck is equipped with an environmental control system to monitor and reduce emissions associated with the charging operation. The environmental control system may comprise a comparative emissions monitor that displays environmental benefits of using the propane-powered generator compared to traditional coal-powered grid electricity.

[0015] According to a further aspect of the disclosed technology, there is provided a method for managing a fleet of autonomous mobile electrical vehicle charging trucks, wherein the method uses a centralized control system to coordinate truck deployment, energy management, and wirelesscommunication protocols for charging electrical vehicles in compliance with anticipated energy regulatory measures.A fleet-based mobile electric vehicle (EV) charging system is disclosed, comprising self-driving trucks with on-board generators powered by eco-friendly propane. The technology mitigates anticipated regulatory constraints on nighttime grid charging during periods when solar farms are inactive. Autonomous navigational capabilities empower the trucks to locate and rendezvous with EVs requiring power, seamlessly delivering charge in motion. Such dynamic charging sidesteps the need for traditional stationary infrastructure and conforms to evolving regulations by offering a versatile, on-demand alternative. Propane's clean combustion underscores this system's environmental advantage over conventional grid reliance, especially during nocturnal hours. Charge initiation is automated through secure wireless communication protocols upon the truck's connection with an EV. Route optimization and scheduling are intelligently managed using artificial intelligence, enhancing both the efficiency and availability of the mobile charging service. The charging trucks provide both safety and reliability when delivering energy to EVs in transit.BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Further features and advantages of the present disclosure will become apparent from the following detailed description, taken in combination with the appended drawings, in which:

[0017] FIG. 1 is a schematic diagram providing an overhead view of a an autonomous mobile electric vehicle charging system, illustrating the operational relationship between a fleet of autonomous propanepowered charging trucks and electric vehicles they service, in accordance at least one embodiment of the present technology;

[0018] FIG. 2 is a perspective view of an autonomous propane-powered charging truck, in accordance at least one embodiment of the present technology, illustrating an exterior illustrating a charging mechanism and navigation equipment;

[0019] FIG. 3A is a cutaway view of the autonomous charging truck of FIG. 2, illustration of a charging interface, in accordance with at least one embodiment of the present technology;

[0020] FIG. 3B is a cutaway view of the autonomous charging truck of FIG. 2, revealing internal components such as a propane fuel system, a generator, an energy storage, and autonomous navigation hardware, in accordance with at least one embodiment of the present technology;

[0021] FIG. 4 is an illustration of a charging interface, demonstrating a connection point between the charging truck and an electric vehicle, suitable for in-motion energy transfer;

[0022] FIG. 5 is a side view of the in-motion charging process, showing the relative positioning of the charging truck alongside the electric vehicle and highlighting the connection between the two during charging, in accordance with at least one embodiment of the present technology;

[0023] FIG. 6 is a flow chart illustrating an Al-driven route optimization process, showing the decision-making method and data inputs used for scheduling and routing the charging trucks, in accordance with at least one embodiment of the present technology;

[0024] FIG. 7 is a representative map illustration displaying a simulated deployment of charging trucks using an Al optimization routing to service multiple EVs across a geographic region;

[0025] FIG. 8 is a schematic diagram of an energy transfer mechanism, in accordance with at least one embodiment of the present technology, illustrating a control system and electrical components that facilitate the flow of power from the propane generator to the electric vehicle's battery;

[0026] FIG. 9 is a block diagram illustrating a wireless communication protocol process, showing stages of automatic initiation of charging after the autonomous connection has been established between the truck and EV;

[0027] FIG. 10 is a diagram representing the sensory and guidance systems equipped on the autonomous charging truck, detailing the components involved in navigation and safety features that allow for collision avoidance;

[0028] FIG. 11 is an illustrative diagram of the propane storage and fuel delivery system within the charging truck, depicting tanks, fuel lines, and refilling connections;

[0029] FIG. 12 is a block diagram of the central control system, showing integration with vehicle operation controls, energy management systems, and central fleet management communications;

[0030] FIG. 13 is a graphical side-by-side comparison of the environmental impact of traditional coal- powered grid electricity versus propane for mobile EV charging, showcasing emission reductions and sustainability benefits;

[0031] FIG. 14 is an illustrative chart that highlights the system's adaptive capabilities in response to anticipated energy regulations, demonstrating how the mobile charging infrastructure can provide flexibility within regulatory constraints; and

[0032] FIG. 15 schematically illustrates charging of an electric aircraft by a charging aircraft, in accordance with various embodiments of the present technology.

[0033] Throughout the drawings, identical reference numerals denote identical or functionally similar elements.DETAILED DESCRIPTION

[0034] Various aspects of the present disclosure generally address one or more of the problems of developing mobile, efficient, and grid-independent charging solutions that resolve the limitations of the prevailing conventional fixed station charging models and systems.

[0035] One of the foremost challenges with grid charging electric vehicles (EVs) at night is the decreased availability of renewable energy sources. Solar power, a key renewable energy contributor, is inherently variable and dependent on daylight hours. Consequently, its absence at night leads to a gap in supply, requiring the grid to lean more heavily on non-renewable energy sources, potentially diminishing the overall environmental benefits of using EVs.

[0036] The potential for regulatory action aimed at curbing night-time grid charging complicates matters further. Such regulations are motivated by the need to balance the electrical grid and maintain its stability. Regulatory limitations on night-time charging could become more prevalent, specifically to steer consumption towards periods when renewable energy production is high, thus fostering a better alignment with green energy goals.

[0037] Additionally, night-time charging places incremental stress on the power grid during peak hours. T raditiona lly , energy consumption drops at nighttime, but as more EVs come online, the heightened demand for overnight charging may shift the peak load timing, leading to increased strain on the power infrastructure. Given that residential power usage also tends to spike in the evening as people return home from work, overlapping EV charging demands can exacerbate the strain, potentially leading to greater grid instability, increased reliance on fast responding, but often less eco-friendly peaker plants, and higher electricity costs for consumers.

[0038] These issues underscore the need for innovative solutions that augment the grid's capacity while promoting the use of renewable energy. Approaches that may circumvent the obstacles associated with night-time grid charging — whether through technology that leverages stored solar energy, alternative off-grid power supplies, or through scheduling frameworks that better distribute charging loads — would represent a significant advancement in EV infrastructure.

[0039] Autonomous vehicle technology represents one of the most significant advancements in the transportation sector, promising to redefine mobility ecosystems through enhanced convenience, efficiency, and safety. Systems relying on sensors, cameras, LIDAR, radar, and advanced algorithms may enable vehicles to perceive their environment, make real-time navigational decisions, and travel with limited or no human intervention. Despite advancements in the autonomous vehicle technology, conventional autonomous navigation systems still face substantial limitations. Driving in complex urban environments, handling unpredictable scenarios, navigating adverse weather conditions, and complying with the myriad rules of the road continue to be significant technological challenges. The algorithms thatgovern autonomous behaviors need to be robust enough to handle the vast uncertainty inherent in real- world conditions.

[0040] Moreover, safety concerns remain a critical issue. Ensuring that autonomous vehicles can reliably detect and respond to obstacles, pedestrians, and other vehicles is paramount. Any system failure could result in accidents, raising considerable concern about the ability of these systems to consistently safeguard human life.

[0041] Coordination among a fleet of autonomous vehicles engenders an additional layer of complexity. Managing numerous self-driving vehicles in a cohesive and unified manner, such as coordinating their routes to prevent congestion or to ensure equitable service distribution, is a substantial logistical challenge. In a world where autonomous fleets become common, sophisticated management systems are needed. These management systems need to ensure that vehicles not only operate safely and effectively on an individual basis, but also contribute positively to the broader traffic ecosystem.

[0042] To address these issues, an advancement in machine learning techniques, sensor fusion, and vehicular communication systems, as well as rigorous safety testing and validation processes are needed. The technology as described herein aims to close the gap between the current capabilities of autonomous navigation systems and the aspirational goals of fully autonomous transportation networks that operate seamlessly and safely.

[0043] The environmental impact of electric vehicles (EVs) is closely linked to the ecological footprint of the charging methods employed to power them. As the transition from traditional internal combustion engines to EVs accelerates, understanding and optimizing the sustainability of EV charging becomes increasingly critical. Charging methods vary widely, from grid-tied electricity to off-grid, renewable-driven systems. The carbon footprint of these methods is strongly influenced by the energy mix of the power sources. For EVs to truly deliver environmental benefits, the electricity utilized for charging must come from low-emission sources.

[0044] A comparative analysis between the emissions generated by coal-powered grid electricity and propane reveals distinct environmental implications. Coal-powered electricity, traditionally a staple of energy grids globally, is notorious for its high greenhouse gas emissions, particularly carbon dioxide. Additionally, coal combustion also releases other harmful pollutants, including particulate matter, sulfur dioxide, and nitrogen oxides, which can lead to air quality issues and health concerns.

[0045] In contrast, propane is a cleaner-burning fossil fuel, emitting significantly fewer pollutants and greenhouse gases when combusted. While not a zero-emission energy source like wind or solar, propane offers several advantages: it produces less carbon dioxide than coal, nearly negligible particulate emissions, and lower levels of sulfur dioxide and nitrogen oxides. As such, utilizing propane for on- demand mobile EV charging could represent a more environmentally-friendly alternative to grid-based charging, particularly in regions where the energy grid is predominantly coal-powered.

[0046] It is crucial to consider not only the direct emissions from the fuel source but also the efficiency of the energy conversion process and the full lifecycle emissions — from extraction and production through end-use. In this light, while propane does not reach the carbon neutrality of renewable resources, it serves as a transitional fuel that can reduce the ecological impact of EV charging, especially as grid decarbonization efforts continue.

[0047] Strategies that enable the integration of lower-emission fuels like propane for EV charging are instrumental in reducing the environmental footprint of the transportation sector. This is particularly important as societies aim for more sustainable transportation solutions without exacerbating the existing load on the electrical grid, all while striving to meet stringent emission reduction targets to combat climate change.

[0048] Artificial Intelligence (Al) has become a cornerstone in the management of fleet operations, offering sophisticated tools to optimize routes, enhance scheduling, and improve overall efficiency. Traditional methods for route optimization often relied on static algorithms that considered a limited set of predictable variables, such as distance and estimated times of travel. However, the rise of Al has allowed for much more dynamic and complex analyses. Today's Al-enhanced route optimization methods can process large datasets in real-time, accounting for an array of ever-changing factors such as traffic patterns, weather conditions, construction detours, and even driver behavior. These systems make use of machine learning to continuously improve their predictions and suggestions, becoming more accurate and reliable over time. In the realm of predictive scheduling, Al plays an indispensable role by using historical data to foresee future demands and requirements. It allows for anticipatory decision-making that can provision resources before they're needed, significantly reducing wait times and improving service levels. With real-time decision-making capabilities, Al systems can adjust plans on the fly in response to unforeseen events, ensuring fleet operations can adapt to any situation at a moment's notice.

[0049] Despite these advancements, using Al in conventional fleet management has shown limitations. One major challenge is the quality and quantity of data required for Al algorithms to function effectively. Faulty, sparse, or irrelevant data can lead to incorrect predictions and suboptimal decisionmaking. Another limitation is the need for extensive computational resources to process the complex algorithms and large datasets, which may not be readily available to all fleet operators. Moreover, while Al systems are exceptionally good at handling tasks that they've been trained for, they may struggle with entirely novel scenarios that fall outside their programmed models. This can lead to performance issues when encountering situations that aren't represented in the training data. There's also a level of unpredictability inherent in Al decision-making, as the reasoning processes of such systems are not always transparent or explainable to human operators, leading to trust and usability issues.

[0050] Finally, the integration of Al into conventional fleet mobility and energy management systems requires significant upfront investment in technology and expertise. This may impose barriers to entry forsmaller operators orthose in markets that are more price sensitive. Despite such limitations, Al's potential to revolutionize fleet management continues to drive innovation, with ongoing research and development aimed at overcoming these challenges and unleashing the full benefits of Al in this field.

[0051] The electric vehicle (EV) industry stands at the precipice of significant transformation, where the accelerating adoption of EVs ushers in new opportunities for improvement in charging technologies. As the market expands, there is an increasing need for flexible, on-demand charging solutions that can supplement the current fixed charging infrastructure. Fixed charging stations, while critical to the foundation of the EV ecosystem, cannot single-handedly address the growing and diverse needs of all EV drivers, especially those who face logistical constraints or reside in areas with insufficient charging coverage.

[0052] The demand for independence from the conventional power grid for EV charging is also on the rise. An independent power source for EV charging could alleviate many of the challenges faced by grid-tied systems, such as limitations on charging times due to peak electricity demand or time-of-use (TOU) rates that discourage charging at certain hours. Independent power sources, such as propanepowered generators, could enable charging in a wider range of locations and conditions, thereby enhancing the convenience and appeal of owning and operating EVs.

[0053] Furthermore, there are significant environmental and regulatory incentives driving the development of alternative charging methodologies. As governments around the world enact stricter emissions targets and provide incentives for renewable energy integration, the EV charging industry must adapt to align with these goals. Alternative methodologies that utilize cleaner fuels, such as propane, or that can be seamlessly integrated with renewable energy sources may help reduce the carbon footprint of EV charging operations. Additionally, such approaches may better position the EV industry to comply with future regulations that may restrict grid charging during periods of high demand or low renewable energy production.

[0054] Ultimately, the traditional model of EV charging is ripe for innovation, and the industry has the potential to benefit substantially from systems that offer on-demand, mobile, and clean-energy-powered charging solutions. By addressing current gaps in the infrastructure, anticipating future regulatory landscapes, and prioritizing environmental sustainability, the EV charging industry has the opportunity to improve accessibility, convenience, and adoption rates of electric vehicles significantly.

[0055] The technology as described herein represents a groundbreaking innovation in the realm of electric vehicle (EV) charging services by introducing a fleet of autonomous trucks, each outfitted with clean-burning propane-powered generators. These mobile charging units challenge the status quo of EV charging by offering the unique capability to deliver on-demand power to vehicles wherever they are, even while in motion. As such, the system as disclosed herein transcends the limitations of traditional stationary infrastructures and presents a paradigm shift in how electric vehicles receive power.

[0056] The utilization of propane as the energy source for these autonomous charging trucks is a deliberate choice aimed at maximizing environmental benefits. Propane's clean-burning properties set it apart from conventional fossil fuels, as it emits fewer greenhouse gases and pollutants. Consequently, these mobile chargers may be seen as a more sustainable alternative, one that is better aligned with contemporary eco-conscious values and regulatory trends pushing for reduced emissions.

[0057] Perhaps most distinguishing is the charging trucks’ ability to navigate to and connect with EVs autonomously while both vehicles are in transit. This function not only enhances the convenience and efficiency of the charging process for EV drivers but also represents a significant technical achievement, bridging the domains of autonomous vehicle technology and advanced charging systems. By enabling charging on the go, the technology disclosed herein addresses critical pain points for EV drivers, such as range anxiety and the unavailability of nearby charging stations.

[0058] Moreover, the system's streamlined integration with Al algorithms for route optimization reflects a broader commitment to operational efficacy and responsiveness to the dynamic demands of fleet management. By leveraging artificial intelligence, the charging trucks can intelligently plan their routes, strategically position themselves based on anticipated demand patterns, and swiftly adapt to realtime requests for charging services.

[0059] The technology described herein positions itself at the forefront of an evolving energy landscape, wherein anticipated regulations may impose restrictions on when and how EVs can draw power from the grid. By offering an autonomous, mobile, and cleaner-burning solution, the disclosed technology provides a forward-thinking response to potential constraints on grid-tied charging. In at least one embodiment, the system embodies a synergy between technological advancement and sustainable practices and may serve as a model for future developments in the EV charging sector, aimed at achieving a cleaner, more efficient, and user-centric energy future.

[0060] The technology described herein combines advancements in artificial intelligence (Al) for route and scheduling optimization, autonomous vehicle technology for navigation and operation, and clean energy technology by using propane as a fuel source for electricity generation. This mobile EV charging approach provides on-the-go, grid-independent charging services for electric vehicles, aligning with energy management strategies and regulatory adaptations, particularly those aimed at optimizing charging times in accordance with renewable energy availability and grid demand.

[0061] The technology as described herein arises in the context of a rapidly growing electric vehicle (EV) market, which is encountering specific bottlenecks that impede its potential for expansion and environmental impact. A principal challenge is the limited reach and convenience of existing fixed EV charging infrastructure. Fixed stations, while forming the backbone of the current EV charging network, are predominantly situated in urban centers. This urban focus leaves vast stretches of rural and remote areas underserved, creating 'charging deserts' and imposing a significant barrier for EV adoption in theselocations. Additionally, the inherent immobility of these stations requires drivers to plan their routes around them, which can be inconvenient and time-consuming.

[0062] As the population of EVs rises, the existing electrical grid is subjected to increasing strain, especially during peak hours. Chargers draw a significant amount of power, and if most EV owners plug in their vehicles at night — when solar power, a primary renewable energy source, is not available — the imbalance between supply and demand can stress grid capabilities. Relying on the grid during these times often leads to increased utilization of less eco-friendly, fossil fuel-based power plants to meet demand.

[0063] There is also a concern about anticipated regulations that may restrict or regulate grid charging of EVs during certain periods, such as nighttime when traditionally electricity generation relies more heavily on non-renewable sources. These regulations could significantly inconvenience users and may even hinder the broader adoption of EVs, as potential owners may be discouraged by the perceived limitations on charging availability.

[0064] Additionally, environmental concerns are at the forefront of the transition to EVs. The overarching goal is to reduce greenhouse gas emissions; however, this benefit is negated when the electricity used to charge the EVs originates from non-renewable sources like coal or natural gas. Griddependent solutions thus find themselves at an environmental crossroads, faced with the challenge of reconciling the environmental promise of EVs with the reality of an energy grid that is not yet fully sustainable.

[0065] While EVs present an opportunity for a more sustainable transportation future, the current trajectory is hindered by issues of accessibility, grid reliability, anticipated regulatory interventions, and environmental implications stemming from the prevalent grid-dependent charging solutions. The technology as described herein is poised to address these challenges by introducing a novel charging system that redefines the conventions of EV power delivery.

[0066] To address the challenges facing the electric vehicle (EV) charging infrastructure, the technology as described herein presents a transformative solution that leverages advanced technologies to deliver a highly adaptive and eco-conscious charging service. The technology relates to a fleet of autonomous trucks, each one a mobile charging unit equipped with its own propane-powered generator capable of providing on-demand electricity to EVs. These self-sufficient charging trucks are imbued with sophisticated autonomous navigation systems, granting them the ability to independently locate and travel to EVs that require a charge. The seamless integration of autonomous technology means that EVs can be charged not just anywhere, but also while in motion — a feature that radically enhances the convenience of EV charging by eradicating the need for stationary charging periods. Alternatively, the technology as described herein may be used by charging aircrafts, which may form a fleet of charging aircrafts, that are configured to charge electric drones or other electric aircrafts.

[0067] Propelling the environmental benefits of the technology is the choice of propane as the fuel source for these mobile generators. As a clean-burning alternative to traditional fossil fuels, propane combustion generates fewer pollutants and greenhouse gases than coal-powered grid electricity. This results in a reduction of carbon footprint and aligns with the sustainable ethos that underpins the EV movement.

[0068] Artificial intelligence (Al) is central to the operation of the fleet. It ensures that the charging trucks are routed and scheduled with unparalleled efficiency, taking into account real-time traffic conditions, the locations of EVs requiring power, and the operational status of each truck in the fleet. Through the application of Al, the system can predict demand hotspots, plan energy distribution effectively, and adapt to changes instantaneously to provide a reliable charging service.

[0069] The incorporation of wireless communication protocols is another advantageous aspect of the technology as described herein and is critical to the launch of the charging process. Upon establishing a connection with an EV, these protocols enable the automatic commencement of charging without manual intervention. This sophisticated communication ensures that the charging session is initiated fluently and securely, further streamlining the user experience.

[0070] The technology as described herein uses autonomous vehicle operation, Al-powered logistics, and clean fuel utilization to overcome the current limitations of EV charging infrastructure. This comprehensive solution not only resolves the present concerns but also sets an innovative trajectory for the future of sustainable transportation and energy management.

[0071] The technology as described herein initiates a paradigm shift in electric vehicle (EV) charging by introducing a system that dramatically enhances the flexibility and convenience of the charging experience. It revolutionizes the standard operating procedure by enabling EVs to receive power on the go, effectively eliminating the downtime often associated with stationary charging practices. This key feature means that drivers can extend the range of their vehicles without the time penalty of waiting at fixed charging stations, thereby addressing one of the significant barriers to EV adoption — range anxiety.

[0072] At the systemic level, the technology as described herein significantly eases the pressure exerted on the electrical grid, particularly during periods of peak demand. By offering an alternate charging solution that operates independently of the grid, the system and methods described herein mitigate the risk of overloading grid capacity — a common concern as the population of EVs increases. This has the dual benefit of ensuring energy availability for EVs without compromising the grid for other users and enables smoother integration of EVs into the energy ecosystem.

[0073] The proactive design of this charging system is attuned to anticipated energy regulations that may restrict traditional grid charging at specific times. As such, this invention promotes regulatory compliance, allowing EV owners and operators to circumvent potential constraints on when they can charge their vehicles. At a period where grid usage may become more regulated, this invention becomesincreasingly vital for maintaining the practicality and appeal of EV transportation. In terms of environmental impact, the system signifies a significant step towards greener EV charging operations. Through the use of clean-burning propane to generate electrical power, the invention stands in stark contrast to coaldependent grid electricity. Not only does it offer a lower-emission charging process, but it also signifies a move towards more sustainable energy management practices. By reducing the reliance on nonrenewable energy sources typically associated with the grid, the invention actively contributes to the overarching effort to decrease greenhouse gas emissions from transportation systems.

[0074] Furthermore, by surmounting existing hurdles associated with EV charging, the invention fosters a more robust adoption rate of electric vehicles. Integrating innovative technologies to enhance user experience, this system directly addresses the concerns prospective EV buyers might have regarding the practicality of EV ownership. In doing so, it aligns perfectly with the trajectory of technological advancement and environmental consciousness in modern transportation, offering a future-forward charging approach that resonates with contemporary consumer needs and ecologically responsible practices.

[0075] The following detailed description of the invention refers to the accompanying drawings that show, by way of illustration, specific aspects and embodiments in which the invention may be practiced. This description will disclose the invention in sufficient detail to enable one skilled in the art to practice it, and it is to be understood that the various embodiments are exemplary in nature and are not all-inclusive. The invention is not limited to the precise arrangements and instrumentalities shown; rather, the invention can be carried out in various ways that are within the scope of the appended claims.

[0076] In the detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be clear to one skilled in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail so as not to obscure the present invention. Embodiments of the invention are described herein, including the best mode known to the inventor for carrying out the invention. Variations of these embodiments may become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventor expects skilled artisans to employ such variations as appropriate, and the inventor intends for the invention to be practiced otherwise than as specifically described herein.

[0077] Moreover, while specific embodiments of the invention have been described, it is understood that the invention extends to all functionally equivalent structures, methods, and uses, such as are within the scope of the appended claims. Additionally, although terms like "primary," "secondary," "front," "back," "top," and "bottom" may be used herein to describe various elements, these terms are not intended to be limiting. The invention could be oriented in any direction and the terminology thus should be interpreted broadly to include such orientations except where explicitly stated otherwise. Throughout this description, the embodiments and examples shown should be considered as exemplars, rather than as limitations onthe present invention. It is also to be understood that the invention is not required to include all the features or advantages discussed, as it may be embodied in various forms, and parts or features of one embodiment may be interchangeably applied to others where technically feasible. Thus, the detailed description and representations of the drawings are intended to convey to those skilled in the art a comprehensive overview of the invention's constructions and functions, without limiting the inventive scope as expressed in the claims that follow this description.

[0078] FIGS. 1-12 illustrate an autonomous charging system 101 for electric vehicles (EVs), in accordance with various embodiments of the present disclosure. The system 101 is designed to address and overcome existing limitations of conventional EV infrastructure. The system 101 comprises one or more self-driving charging trucks 100 (also referred to herein as “a fleet of self-driving charging trucks 100” or a “fleet 100”), each having an onboard clean propane-powered generator 120. Each self-driving charging truck 200 has Al-enhanced routing (provided by the Al routine) and scheduling capability, and the ability to charge EVs while in transit, thus optimizing convenience and efficiency. The system may also have adaptive scheduling capabilities (in other words, is configured to generate adaptive scheduling) that allow(s) the mobile charging trucks to deploy pre-emptively based on predicted demand patterns identified through Al analysis by the Al routine. FIGS. 1 to 14 illustrate components and potential configurations of the system 101 and operational processes therein, illustrating how the system 101 provides a flexible, eco-friendly and grid-independent solution to the challenge of EV charging. FIG. 15 illustrates a method for charging electric vehicles (EVs) using the autonomous mobile charging truck 200.

[0079] In FIG. 1 , the autonomous charging system 101 , an EV charging port 115, autonomous charging trucks 100, an EV 110, onboard propane-powered generators 120, advanced navigation equipment 130, wireless charging connection 140, communication links 150, centralized control system 160, operational zone of charging trucks 170 are illustrated.

[0080] The detailed structure and functionality of the autonomous charging trucks 100 are illustrated in FIG. 2 and FIG. 3, wherein the trucks 100 are shown with detailed labels, highlighting the key components responsible for energy generation, storage, and autonomous navigation. In FIG. 2, autonomous charging truck 200 (exterior view), propane power generation unit 210, autonomous sensors and navigation equipment 220, charging connectors and retractable cabling systems 230, wireless communication transceivers 240, aerodynamic body of the charging truck 250 are illustrated. In FIG. 3, cutaway view 300 of the autonomous charging truck, propane power generation unit (internal view) 310, propane storage tanks 320, autonomous sensors and navigation hardware 330, power control and distribution unit 340, charging interface mechanism 350, wireless communication hardware 360 are illustrated.

[0081] FIG. 4 and FIG. 5 illustrate how a truck 200 provides in-motion charging to EV 110, presenting a non-limiting example of a secure connection between the truck 200 and the EV 110 to facilitate energy transfer safely and effectively. In FIG. 4, an interface mechanism for charging 400, an automatedconnector assembly 410, a precision drive system for connectors 420, a housing and protective casing 430, an array of sensors for connection alignment 440, communication modules 450 are illustrated. In FIG. 5, an autonomous charging truck in charging operation 500, an electric vehicle (EV) in motion 510, a deployable charging arm 520, a charging connector 530, an EV charging port 540, onboard communication devices 550, sensor suite for autonomous operation 560, safety features 570, and energy transfer module 580 are illustrated.

[0082] FIGS. 6 and 7 detail the influence of artificial intelligence on the system 101. Using Al algorithms helps to optimize the operational logistics of the charging truck fleet. Al helps to allocate resources efficiently, anticipate the demand, and adjust the route in real-time, thus providing an adaptive and responsive charging network for the trucks 100. In FIG. 6, Al algorithm process flow chart 600, data gathering stage 610, decision-making phase for optimization 620, route and scheduling instructions 630, real-time monitoring and route adjustments 640, charging optimization and management 650, update and learning cycle for Al 660 are illustrated. In FIG. 7, a map-based visualization of truck deployment 700, electric vehicles requiring charging 710, autonomous charging trucks 200 on route, routing lines for optimized paths 730, Al operational hub 740, charging status indicators 750, predicted demand hotspots 760, and fleet communication links 770 are illustrated.

[0083] Further, FIGS. 8 and 9 delve into the communication and control frameworks that underpin the functioning of the system 101 , comprising the wireless protocols that enable automated charging initiation once a connection is established between the charging truck and an EV. This functionality exemplifies the ability of the system 101 to reduce human intervention and streamline the charging process. In FIG. 8 an energy transfer mechanism schematic 800, a generator unit 810, a fuel supply line 820, a power inverter 830, a charging control module 840, a distribution panel 850, charging connectors 860, safety interlock systems 870, and data and control interface 880 are illustrated. In FIG. 9, a communication protocol schematic 900, truck's wireless communication module 910, communication handshake 920, EV's communication unit 930, a truck in communication with EV 940, EV responding to communication 950, central control system monitoring 960, feedback mechanism for status updates 970, and conclusion of charging session communication 980 are illustrated.

[0084] FIGS. 10-12 illustrate sensory and guidance systems configured to ensure the charging trucks 100 operate safely within various environments and traffic conditions, thus contributing to safety and reliability of the system 101 . In FIG. 10, safety and autonomous operation systems 1000, autonomous driving sensor suite 1010, an autonomous navigation control module 1020, vehicle safety systems 1030, vehicle diagnostics and communication interface 1040, emergency control systems 1050, energy management controls 1060, secure communication protocols 1070, and user interface and control panel 1080 are illustrated. In FIG. 11 , a propane fueling system 1100, propane storage tanks 1110, fuel supply line 1120, propane vaporizer 1130, generator unit 1140, fuel management system 1150, safety and containment subsystem 1160, refueling connection point 1170 are illustrated. In FIG. 12, central controland management systems 1200, a central processor 1210, a navigation subsystem 1220, an energy management system 1230, a safety management module 1240, a charging control system 1250, a fleet communication network 1260, user interfaces and diagnostic consoles 1270, and an external communication gateway 1280 are illustrated.

[0085] In addition to these practical and technical advantages, the system 101 is also conceived with an acute awareness of the environmental implications of EV charging. As such, FIGS. 13 and 14 illustrate a visual comparison of emissions associated with conventional charging methods versus the proposed propane-powered approach, highlighting the significant environmental benefits derived from the technology as described herein. FIG. 13 illustrates: an environmental benefits comparative chart 1300, emissions from conventional coal-powered sources 1310, reduced emissions from propane-powered generators 1320, delta comparison of emissions 1330, legend and metrics explanation 1340, and graphical representations of additional benefits 1350. FIG. 14 illustrates: regulatory compliance and adaptability chart 1400, timeline of grid charging restrictions 1410, mobile charging fleet operational summary 1420, Al-enabled dynamic routing and scheduling advantage 1430, depiction of environmental and grid benefits 1440, and narrative elements on wireless communications management 1450.

[0086] Collectively, the embodiments represented within FIGS. 1-14 provide a window into the diverse capabilities and potential implementations of the novel EV charging system 101 as described herein, serving as embodiments reflecting the spirit and scope of the invention, but not its entirety. It is to be understood that the invention may assume various alternative embodiments and that each specific embodiment described herein is intended to be illustrative, not limiting or exhaustive.

[0087] Referring now in detail to the drawings, where like reference numerals refer to like elements throughout, FIG. 1 illustrates a schematic overview of an autonomous electric vehicle (EV) charging system 101 , in accordance with the embodiments of the present invention. The system 101 is designed to provide mobile, on-demand charging services to EVs 110 using at least one autonomous charging truck 200 (fleet 100 of trucks), each charging truck 200 being self-navigating and propane-powered (and therefore may be referred to herein as “propane-powered charging truck 200”).

[0088] FIG. 1 illustrates a relational architecture between the fleet of autonomous charging trucks 100 and a plurality of electric vehicles (EVs) 110 that may be in need of charging. Each charging truck 200 has an onboard clean-burning propane generator 120, capable of providing electrical energy to EVs. The role of the onboard generator 120 is central to the truck's ability to offer a stand-alone charging solution that is freed from the limitations of grid dependence.

[0089] FIG. 1 also denotes an advanced navigation equipment 130 positioned on each truck 200, which allows for autonomous movement and precise operation of the trucks 100 within varying traffic conditions and terrains. This equipment is used for facilitating the trucks' autonomous journey to the EVs 110 requiring charging services and for ensuring safe operation while they are in motion. The interactionbetween the trucks 100 and EVs 110 is further represented by wireless connection(s) 140. In at least one embodiment, the charging process is initiated automatically once proximity is achieved.

[0090] Also illustrated in FIG. 1 are visual representations of communication links 150 that connect the charging trucks 100 not only with EVs 110 but also with a centralized control system 160. The centralized control system 160 plays a crucial role in leveraging artificial intelligence to enhance the routing and scheduling operations for the fleet. By judiciously optimizing logistics, the system 101 maximizes both the efficiency and availability of the mobile charging service. The centralized control system 160 is configured to coordinate truck deployment, energy management, and wireless communication protocols for charging electrical vehicles in compliance with anticipated energy regulatory measures.

[0091] As seen in FIG. 1 , the charging trucks 100 are distributed within an operational zone 170, indicating the scalability and coverage potential of the fleet of trucks 100 across different geographic locales. The Al-optimized dispatching of the trucks 100 targets EVs 110 in multiple locations, including urban centers, highways, and remote areas, further underlining the flexibility of the system 101 and responsiveness to EV drivers’ charging needs.

[0092] This top-down view in FIG. 1 sets the foundational stage for understanding the various interlocking components and processes that comprise the inventive mobile EV charging system 101 . The aforementioned reference numerals in FIG. 1 correspond to additional detailed views and operational explanations provided in subsequent drawings and related descriptions within the present description.

[0093] FIG. 2 illustrates a perspective view of the autonomous propane-powered charging truck 200, in accordance with at least one non-limiting embodiment of the present disclosure. The charging truck 200, is a component of the autonomous mobile electric vehicle charging system 101 illustrated in FIG. 1. FIG. 2 illustrates the charging truck's external features, elements, and components configured to enable autonomous mobility and on-demand charging.

[0094] The charging truck 200 is shown equipped with a robust, self-contained power generation unit 210, where propane combustion is used to generate the electrical energy needed for EV charging. The propane storage tanks are safely housed within the vehicle's framework, constructed to comply with regulatory safety standards, and easily accessible for refueling purposes. The power generation unit 210 is seamlessly integrated into the truck 200 to ensure maximum space efficiency while maintaining the vehicle's balanced weight distribution.

[0095] Engineered for autonomous operation, the charging truck 200 is fitted with an array of sophisticated sensors and navigation equipment 220 identified on various points of the exterior. These may include, but are not limited to, light detection and ranging (LIDAR), radar, cameras, and global positioning system (GPS) modules that collaborate with each other to generate a comprehensive understanding (comprising, for example, a picture) of the vehicle's operational environment. The sensorarray formed by the sensors and navigation equipment 220 is used for allowing the truck 200 to navigate to and align with EVs 110 in need of charging services. The sensors and navigation equipment 220 form an autonomous navigation system of the charging truck 200 (and of the charging aircraft 1500 of FIG. 15).

[0096] Prominently displayed charging connectors and retractable cabling systems 230 are strategically positioned on the side of the vehicle to facilitate a streamlined connection with various EV charging ports. Illustrated in an extended state ready for engagement, the interfaces implemented with the charging connectors and retractable cabling systems 230 underscore the charging truck's adaptability to various models of EVs 110 and charging standards.

[0097] To facilitate the automated initiation and management of the charging process, wireless communication transceivers 240 are provided on the charging truck 200. The wireless communication transceivers 240 ensure secure communication between the truck 200, the EVs 110 requiring charge, and the centralized control system 160 operating the fleet of charging trucks 200.

[0098] The charging truck 200 also has an aerodynamically optimized body 250, conceived with mobility and energy efficiency in mind. Such design considerations are vital for reducing drag and optimizing fuel economy during transit, which, in turn, enhances overall operational efficiency and sustainability.

[0099] FIG. 2 illustrates one possible embodiment of the autonomous charging truck 200 within the scope of the present disclosure. FIG. 2 conveys how the charging truck 200 serves as a foundational element in the mobile charging system 101 configured to addressing the needs of current and future EV drivers by offering a versatile and eco-friendly charging solution on the go. Additional embodiments and configurations may exist, reflecting variations in design, componentry, and functionality, as described elsewhere in this application or as may be envisioned by those skilled in the art.

[0100] FIG. 3A illustrates a see-through portion of the autonomous propane-powered charging truck 300, which is a part of the mobile EV charging fleet system 101. FIG. 3A illustrates the internal layout, highlighting the intricate arrangement of components that synergize to facilitate the truck’s autonomous charging capabilities.

[0101] Foregrounded in this depiction is the propane power generation unit 310 positioned within the charging truck 300, demonstrating the compact yet efficient configuration that houses the propane engine and the electricity generator. This power generation unit 310 is configured to convert propane into electrical energy to charge the EV batteries of the EVs 110.

[0102] Propane storage tanks 320 are securely installed on the autonomous propane-powered charging truck 300, surrounding the power generation unit 310, with consideration for safety and accessibility in mind. These storage tanks 320 are configured to meet stringent safety codes and areequipped with advanced pressure management systems to ensure safe operations under all standard operating conditions. The propane storage tanks 320 form a propane fuel storage system.

[0103] The autonomous sensors and navigation hardware 330, illustrated in FIG. 3B, enable autonomous operation and allow the truck 300 to integrate advanced technologies for self-driving functionality. The components of the sensor array 330 — which may comprise, for example, LIDAR, radar, optical cameras, and GPS — work in concert to guide the autonomous propane-powered charging truck 300 through various environments to its target destinations.

[0104] Central to the truck’s internal structure is the control and distribution unit 340 that regulates the flow of electricity from the generator to the charging apparatus. This control and distribution unit 340 uses Al algorithms configured to optimize routes and scheduling, generating Al-optimized routes and controlling operational decisions (ensuring that the operational decisions are effectively implemented). The charging truck 200 is thus navigated to the electric vehicle 110 based on the Al-optimized routes.

[0105] Prominent in FIG. 3A is the representation of the charging interface 350, which includes the retractable charging cables and the mechanism for managing the connection to EVs 110. When activation occurs, the charging interface 350 serves as the point of energy transfer, delivering charge to the EVs 110 with minimal loss and maximum safety. Also depicted is the wireless communication hardware 360 that provides linkage between the truck 300, EVs 110, and the central system 160, facilitating ongoing communication necessary for coordination, safety, and transaction management.

[0106] FIGS. 3A, 3B illustrate the functional composition of the mobile charging truck 300, emphasizing that while the exterior supports autonomous navigation and engagement with EVs 110, the interior is a powerhouse of energy generation, management, and delivery capabilities. The encapsulation of these components within the autonomous truck 300 demonstrates how the technology as described herein harmonizes complex systems to provide a forward-thinking solution to EV charging challenges. While FIGS. 3A, 3B demonstrate one embodiment, other configurations or structural adaptations that fall within the breadth of the disclosed technology may exist.

[0107] Turning now to FIG. 4, this illustration provides a detailed view of the interface mechanism 400 (also referred to herein as an “interface mechanism for charging 400”) that plays a critical role in the transient energy transfer process between the autonomous charging truck 200 and an electric vehicle (EV) 110. FIG. 4 focuses on illustrating physical attributes and operational features of the charging truck 200 of charging connection system designed to initiate and sustain the charging session.

[0108] The interface mechanism 400 has an automated connector assembly 410 configured to safely extend and retract to bridge a gap between the charging truck 200 and a recipient EV 110. The connector assembly 410 is configured to accommodate a variety of charging standards and types of EV ports 115 of the EVs 110, featuring adaptable attachments that securely lock into place once engagement with the EV charging port 115 is achieved.

[0109] FIG. 4 also illustrates a precision drive system 420 (also referred to herein as a “precision drive system for connectors 420” or a “drive system 420”) that enables the controlled movement of the connector assembly 410. This drive system 420 is configured to accurately extend and retract the connectors, managing their motion to align with the EV charging port's of the EVs 110 specific position and configuration, ensuring a reliable and efficient connection suitable for high-speed energy transfer.

[0110] FIG. 4 also illustrates the housing and protective casing 430 that encompasses the connector assembly 410 and the precision drive system 420. This housing and protective casing 430 serves multiple purposes: it secures the internal components from environmental factors, ensures user safety by preventing unintentional contact during operation, and promotes longevity of the apparatus through robust design. Integrated into the interface mechanism 400 is an array of sensors 440 (also referred to herein as an “array of sensors for connection alignment 440”) that facilitate the autonomous alignment and connection process by detecting the proximity, orientation, and engagement status with the EV’s charging port. The multiple sensors 440 provide real-time feedback to the truck’s control systems, allowing for adjustments necessary to establish an optimal and secure charging connection. This allows to autonomously establish a charging connection with the EV.

[0111] Furthermore, communication modules 450 embedded within the interface mechanism 400 are responsible for exchanging data and control signals with the EV 110. These communication modules 450 enable coordination with the EV's onboard systems to authenticate the charging session, synchronize the energy transfer, and monitor the charging progress, ensuring that the charging operation is carefully managed and controlled. The communication modules 450 provide wireless communication between the electric vehicle and the charging truck to synchronize and control the charging session.

[0112] In the embodiment illustrated in FIG. 4, it is evident that the charging interface mechanism 400 is engineered to seamlessly integrate with the overall function of the autonomous charging truck 200. Each of the described components contributes to a safe, efficient, and user-friendly in-motion charging experience, thus underpinning the inventive aspects of the mobile charging solution. While FIG. 4 depicts one embodiment of the interface mechanism, the system 101 contemplates various other designs, mechanisms, and methods that enable robust, accurate, and flexible connections for mobile EV charging without departing from the scope and spirit of the invention.

[0113] FIG. 5 illustrates a side view of the mobile charging process in operation as engaged by the autonomous propane-powered charging truck 200 and an electric vehicle EV 110 in need of charging. FIG. 5 illustrates the dynamic charging capability that distinguishes the system 101 as described herein from conventional stationary charging methods. In this embodiment, the charging truck 200 is shown in close proximity to the EV 110, illustrating the physical arrangement necessary for the autonomous initiation of the charging session. The truck 200 comprises a deployable charging arm 520 that extends towards the EV 510 with the charging connector 530 ready to interface with the EV's charging port 540.The charging arm 520 and charging connector 530 have sufficient reach and flexibility to maintain a secure energy transfer link while both vehicles (the truck 200 and the EV 110) are in motion.

[0114] Complementing the charging apparatus, both the truck 200 and EV 510 are equipped with dedicated communication devices 550 to support the exchange of data, ensuring synchronization of charging parameters and real-time adjustment of the connection throughout the charging session. The communication devices 550 manage the complex data interchange required for safe and efficient inmotion charging. The charging truck 200 demonstrates advanced autonomous functionalities through its sensor suite 560 positioned strategically around its chassis. These sensors 560 continuously gather environmental and situational data to safely guide the vehicle alongside the EV 510, enabling the precise alignment needed for the charging process.

[0115] To ensure the integrity of the charging operation and the safety of all on-road participants, various safety features 570 on both the charging truck 200 and EV 510 are present, such as collision avoidance systems, automatic emergency braking, and real-time monitoring systems, that oversee the charging process.

[0116] FIG. 5 further illustrates an energy transfer module 580 visualized within the truck 200, controlling and managing the flow of electricity from the propane-powered generator to the EV 510. This energy transfer module 580 embodies the energy management strategy that underlies the inventive system, regulating the charging rate based on the EV's immediate needs and battery status.

[0117] FIG. 5 illustrates a moment during the in-motion charging process, illustrating how the charging truck 200 and EV 510 function cohesively to realize a mobile charging solution that brings unparalleled convenience and enhanced utility to the EV charging infrastructure landscape. Advantageously, as illustrated in FIG. 5, the system 101 and method as described herein provide on-the- go charging without the need for EVs 110 to convene at conventional stationary charging locations. While FIG. 5 presents a non-limiting example of scenario of the in-motion charging process, the underlying principles and technological aspects detailed may be adapted to various configurations and operational contexts within the scope of the invention.

[0118] FIG. 6 illustrates artificial intelligence-driven component of the technology as described herein, more specifically illustrating a flow chart of a method 600 that illustrates logic and sequential steps executed by the Al routine for route optimization and scheduling of the autonomous propane-powered charging trucks 200 that form the EV mobile charging fleet 100. The Al routine is configured to generate Al-optimized routes and adjust truck routes in real time in response to traffic conditions and demand distribution.

[0119] At step 610, the Al routine first gathers data from a multitude of sources, including real-time traffic updates, GPS tracking information of both the fleet 100 of charging trucks and EVs 110 requiring charging services, and historical charging patterns to predict future demand effectively.

[0120] From there, the Al routine enters a decision-making phase at step 620, in which it analyzes the gathered data using machine learning techniques to make informed predictions about the most efficient routes and schedules for the trucks. This determination considers factors such as the proximity of trucks 200 to EVs 110, predicted traffic conditions, and anticipated charging needs.

[0121] Upon completing the route optimization, the system 101 then proceeds to issue instructions to individual trucks 200 at step 630, including specific directives for the optimal paths to follow, the EVs 110 to target for charging services, and the expected journey times. This tailored route dispatch aims to minimize travel time, conserve fuel, and maximize the number of EVs serviced.

[0122] As the trucks navigate their assigned routes, the Al routine continues to monitor their progress and any emerging situations that may necessitate a route adjustment at step 640. This may involve rerouting the truck 200in response to sudden changes in traffic patterns, shifts in EV demand, or unexpected road closures.

[0123] Concurrent with truck navigation, the Al routine is also configured to maintain ongoing optimization of the charging process at step 650. It optimizes charging duration, power output, and even anticipates future charging stop locations based on the current state of the fleet 100 and the continual inflow of data.

[0124] Upon successful completion of the charging service to an EV 110, the system 101 prepares for the next cycle of optimization at step 660, updating its internal models with the most recent data gathered during the operation, including customer feedback, power expenditure, and route efficiency. This perpetual learning and refining loop enable the Al to continuously improve its predictive accuracy and operational efficiency.

[0125] The steps 610-660 of the method 600 are executed by the Al routine of an Al module of the system 101. The Al module is configured to optimize routes and scheduling of the charging trucks based on demand and traffic conditions. The Al routine of the Al module uses the centralized control system 160 and truck computer hardware to implement.

[0126] FIG. 6 illustrates the intelligence and adaptivity of the system 101 , highlighting how the integration of artificial intelligence into fleet management ensures the inventive mobile EV charging solution is both proactive and responsive — characteristics crucial for high scalability and customer satisfaction in urban and suburban environments alike. The employment of the method 600 depicted in FIG. 6 denotes a sophisticated approach to the logistical challenges of fleet-based mobile charging, underscoring the inventive steps taken to bring forth a system that is both innovative and reflective of the dynamic needs of the modern-day EV market.

[0127] FIG. 7 illustrates representation 700 of the deployment of the autonomous propane-powered charging trucks 200 across a geographic area, demonstrating the practical application of the Al algorithmsfor route optimization and scheduling as introduced in FIG. 6. This map-based visualization underscores the strategic positioning and distribution tactics facilitated by Al which form the bedrock of the mobile charging service's efficacy and responsiveness.

[0128] FIG. 7 depicts a plurality of electric vehicles EVs 710, each at various locations within a service region, which may include urban centers, highways, and rural areas. The charging trucks 200, each autonomously navigating the landscape, are shown actively en route to or in the process of charging these EVs. The paths of the trucks 200 are dynamically adjusted by the Al-driven system, represented in FIG. 7 by various routing lines 730 that signify the flexibility and adaptability of the truck's movement in real time.

[0129] FIG. 7 also illustrates an Al operational hub 740, which functions as the processing and command center for the autonomous fleet. This hub collects and synthesizes data — such as vehicle locations, charging levels, and real-time traffic information — before employing advanced machine learning techniques to optimize charging truck deployment across the service region.

[0130] In the interest of efficient energy management, the FIG. 7 further illustrates indicators of charging status 750 associated with the EVs 710, providing a snapshot of the demand distribution that the Al hub 740 uses to predict and orchestrate the fleet's movements. Additionally, potential hotspots for charging demand 760, predicted by the Al to expect increased charging activity, are also visualized, dictating pre-emptive redeployment of trucks to those areas to satisfy the anticipated need.

[0131] Wireless communication links 770 are also illustrated in FIG. 7. The wireless communication links 770 provide the seamless data exchange between the EVs 710, the charging trucks 200, and the Al operational hub 740. These connections enable continuous monitoring and dynamic reconfiguration of routes and charging schedules to reflect the evolving landscape of energy requirements.

[0132] FIG. 7 thus illustrates the systemic approach taken by the technology as described herein to intelligently connect charging trucks 200 with EVs 110 across widespread and varied locales. The technology as described herein allows to bring mobile charging services directly to EVs, optimizing operations to cater to demand efficiently, and minimizing downtime for drivers waiting for accessible charging stations.

[0133] The embodiment depicted in FIG. 7 is one example of the Al-optimized fleet deployment according to the present invention, yet the technology as described herein is not confined to this single representation. Various operational models, replete with different charging strategies and technical nuances, can be realized within the full inventive scope of the system 101 as described herein, further detailing the adaptability and breadth of the mobile charging concept as a whole.

[0134] FIG. 8 illustrates a detailed schematic diagram 800 of the energy transfer mechanism intrinsic to the operation of the autonomous propane-powered charging trucks within the mobile EV charging fleet.This diagram 800 meticulously outlines the components that manage the conversion and delivery of energy from the propane fuel source to the EVs in need of charge. Central to the energy transfer process is a generator unit 810, which is fueled by clean-burning propane. The generator unit 810 is responsible for converting chemical energy stored in propane into electrical energy that can be used to recharge EV batteries. Depicted adjacent to the generator unit 810 is the fuel supply line 820, which ensures a continuous delivery of propane from the truck’s storage tanks (not shown) to the generator.

[0135] Electrical output from the generator unit 810 flows through a power conversion system 830, which includes both an inverter and a rectifier. This versatile component is for adapting the raw alternating current (AC) supplied by the generator to the appropriate form — either AC or direct current (DC) — for the EV charging systems. The power conversion system handles voltage conversion, regulation, stabilization, and, if necessary, inversion or rectification to ensure that the electrical output safely matches the specifications required by various EV batteries, which may require AC for Level 1 or Level 2 charging, or DC for fast charging applications.

[0136] Following the inversion process, the conditioned electrical current is directed to the charging control module 840, a sophisticated system that manages the charging parameters such as current flow rate, charging duration, and safety checks. The charging control module 840 interfaces with onboard diagnostics and synchronization systems to precisely tailor the charging output to each EV's accepted charging profile.

[0137] The distribution panel 850 is the subsequent stage depicted in the schematic, serving as the junction where electrical energy is channeled to multiple charging connectors 860. These connectors are configured to mate with a range of EV charging ports, ensuring compatibility with different vehicle models and standardized charging interfaces.

[0138] Safety mechanisms integrated into the energy transfer system, illustrated here as a safety interlock 870, play a vital role in preventing overloading, short-circuiting, or any energy discharge events that may pose safety concerns. The safety interlock 870 operates in concert with real-time monitoring systems to ensure that charging occurs within predefined safety parameters. Lastly, the system as described herein includes a data and control interface 880 that communicates with the EV during charging to monitor the status, transfer energy usage data, and receive commands that might adjust charging as vehicles' battery states change over the charging session.

[0139] FIG. 8 thus illustrates the well-orchestrated electrical architecture that enables these mobile charging units to deliver energy safely, efficiently, and adaptively to EVs, mitigating the need for grid connectivity. FIG. 8 explicates how the system as described herein seamlessly integrates various electrical components to bolster a new frontier of on-the-go charging - ensuring the functionality extends beyond simple energy provision to include a harmonized charging experience, fully attuned to the nuances of modern electric mobility.

[0140] It should be recognized that while FIG. 8 depicts one embodiment of the energy transfer mechanism within the mobile charging truck, the present technology may be embodied in various forms of energy conversion, management, and delivery. The spirit and scope of the technology as described herein encompasses potential variations in design that offer similar benefits and fulfill the enumerated objective of providing an autonomous, flexible, and environmentally sustainable EV charging solution.

[0141] FIG. 9 illustrates the communication protocol schematic 900 integral to the operation of the autonomous mobile charging system for electric vehicles (EVs), in accordance with various embodiments of the present disclosure. This schematic 900 delineates the critical stages and components involved in the wireless communication that enables automatic charging session initiation upon the successful physical connection between the charging truck 200 and the EV 110.

[0142] The upper portion of FIG. 9 showcases the wireless communication module 910 situated within the charging truck 200. This wireless communication module 910 embodies the hardware and software responsible for broadcasting the truck's presence, its charging capacity, and negotiating the charging session with nearby EVs. It is equipped with the necessary transceivers to establish a secure communication link with comparable systems within EVs.

[0143] The communication handshake 920 as visualized by arrowed lines, represents the bidirectional exchange of information between the truck's wireless communication module 910 and an EV’s corresponding communication unit 930. Through this exchange, identification, authentication, and session parameters are confirmed before energy transfer begins.

[0144] Upon successful handshake and agreement of session parameters via the communication link, the truck 200 (this step is represented by reference numeral 940) automatically commences the electrical coupling process with the EV (this step is represented with arrow 950), establishing a conductive path for electricity to flow from the propane-powered generator to the EV’s battery.

[0145] The central control system 960 of the charging truck 200 monitors the charging process, acting as the overseer for the energy transfer and communication activities. This system 101 ensures that all charging operations, including rate of charging, duration, and termination, are executed according to the predetermined and negotiated session parameters.

[0146] Signal flow lines represent the looping feedback mechanism (implemented at step 970) that transmits real-time charging status updates from the central control system 960 back to the EV 110 via the wireless communication modules of the truck and the EV 910, 930. This ensures both the truck (arrow 940) and the EV (arrow 950) continuously share data about the charging progression, detect any anomalies, and make necessary adjustments or terminate the session as required.

[0147] Depicted at the bottom of FIG. 9, is the final step of communication 980 that signifies the conclusion of a successful charging session. This involves sending the session summary, which includesdetails such as amount of power transferred, duration, and charging efficiency, from the truck (arrow 940) to the EV (arrow 950). This summary may be used for billing, diagnostics, and system improvement purposes.

[0148] FIG. 9 illustrates the wireless communication strategy engrained within the autonomous mobile charging system 101 , detailing how it facilitates a smooth, automated, and safe engagement between the charging truck and EVs. The communication protocol illustrated in FIG. 9 is fundamental to the system's seamless operation, governing the intelligent engagement of charging services that the invention promotes. This protocol showcases not only the ease of interaction but also the heightened level of sophistication in terms of data security, integrity, and compliance with automotive and communication standards. While FIG. 9 presents a specific communication schematic, it should be understood that variations of the described communication protocol may be implemented within the broader scope of the technology as described herein, as long as they fulfill the purpose of enabling seamless, secure, and automated charging transactions between the charging trucks and EVs.

[0149] FIG. 10 illustrates autonomous operation and safety features 1000 incorporated into the propane-powered charging truck 200, which is a component of the mobile electric vehicle (EV) charging system 101. FIG. 10 highlights various systems designed to ensure that the charging truck operates safely, efficiently, and effectively in diverse traffic environments and charging scenarios.

[0150] A centralized array of advanced autonomous driving sensors 1010 is strategically embedded within the truck's structure. This multi-sensor suite, which can include LIDAR, radar, and optical cameras, provides comprehensive situational awareness by continuously scanning the truck's surroundings to gather critical data for navigation and obstacle detection.

[0151] The autonomous navigation control module 1020, which interprets the data received from the autonomous driving sensors 1010, is shown to be the central processing unit. This high-capacity computational core uses sophisticated algorithms to analyze real-time inputs and make immediate driving decisions, guiding the truck safely to its destination.

[0152] Depicted alongside the autonomous navigation control module 1020 are the vehicle’s safety systems 1030, which act in concert with the autonomous sensors. These systems incorporate features such as collision avoidance, lane-keeping assistance, and adaptive cruise control to maintain the truck’s position on the road and avert potential hazards.

[0153] The vehicle diagnostics and communication interface 1040 plays a pivotal role in real-time system health monitoring and inter-vehicle communications. This interface ensures continuous systems checks and facilitates information exchange both within the truck's internal systems and externally with other vehicles, charging infrastructure, and traffic management systems.

[0154] The emergency control systems 1050 are also shown, which include manual override capabilities and automated safety protocols to bring the truck to a safe stop in the event of critical system failures or emergencies on the road.

[0155] In addition, energy management controls 1060 are integrated to oversee the propane consumption, generator output, and battery storage conditions. This ensures that the truck maintains optimal energy levels for both propulsion and charging operations.

[0156] Enforcement of secure communication protocols 1070 is particularly advantageous for preventing unauthorized access, ensuring data privacy, and enabling secure connections for the charging process — a necessary component given the wireless nature of the engagement between the charging truck and client EVs.

[0157] Lastly, the user interface and control panel 1080 permit human operators to monitor operations, input commands, and receive alerts. Although the system is primarily autonomous, this interface provides necessary manual control points for troubleshooting, maintenance, or emergency intervention.

[0158] FIG. 10 emphasizes the comprehensive and integrated approach to safety and autonomy in the design of the charging truck. Each component is carefully considered to contribute to the overall security, reliability, and efficiency of the mobile charging service, addressing the complex operational requirements of autonomous commercial vehicles and the specific challenges of providing mobile EV charging services.

[0159] While FIG. 10 highlights one embodiment of the system’s autonomous operation and safety features, it should be noted that alternative embodiments and variations in the design and implementation of these systems may fall within the scope of the invention. It is understood that the invention contemplates employing any number and combination of similar safety, diagnostic, and control technologies to achieve the objectives set forth.

[0160] FIG. 11 illustrates a propane fueling system 1100 integrated within the autonomous charging truck 200, which is a core component of the inventive mobile electric vehicle (EV) charging system 101. FIG. 11 specifically illustrates the components and subsystems involved in storing, managing, and delivering propane fuel to power the on-board generator unit that supplies electrical energy for EV charging.

[0161] In the center of FIG. 11 , the propane storage tanks 1110 are shown, which serve as the primary fuel reserve for the mobile charging trucks. These propane storage tanks 1110 are engineered to comply with stringent safety protocols, featuring robust construction and equipped with pressure regulation mechanisms to maintain fuel integrity under various environmental and operating conditions.

[0162] Connected to the propane storage tanks 1110 is the fuel supply line 1120, which transports the propane from the tanks to the generator. This supply line includes safety valves and pressure gauges (not explicitly labeled in the figure) to monitor and control the flow of gas, ensuring a smooth and safe transfer of fuel to the power generation unit.

[0163] Adjacent to the fuel supply line 1120 is the propane vaporizer 1130, a device that converts liquid propane into gaseous form before combustion. The vaporizer 1130 is critical for ensuring an optimal combustion process within the generator, facilitating efficiency and reliability in power output.

[0164] The generator unit 1140 is next in line within the fueling system schematic, which illustrates the integral role of the generator in transforming the chemical energy of propane into usable electrical energy for EV charging. It also encapsulates the generator's ancillary components such as the starter, alternator, and cooling system, which all contribute to its sustained operation during charging service delivery.

[0165] Also shown in FIG. 11 is the fuel management system 1150, which oversees the entire propane fueling process, from tank storage to generator feed. This automated system ensures precise control over the flow rate and mixture of propane, adjusting parameters as necessary based on generator demand and operational data.

[0166] To maintain safety and compliance with regulations, the safety and containment subsystem 1160, including emergency shutoff valves and leak detection sensors, is highlighted. This safety and containment subsystem 1160 is configured to minimize the risk of fuel spills, leaks, or unintended release, in order to provide the safest possible operation of the fuel system.

[0167] Lastly, the refueling connection point 1170 is depicted as the interface through which the propane storage tanks 1110 are replenished. This refueling connection point 1170 is accessible, facilitating easy and quick refueling while adhering to safety standards that protect both the equipment and personnel involved in the refueling operation.

[0168] FIG. 11 illustrates a well-conceived propane fueling system that provides a reliable and sustainable power source for the autonomous mobile charging trucks 200, exemplifying a useful step in achieving an environmentally friendly alternative to traditional grid-dependent EV charging infrastructures.

[0169] While the components illustrated in FIG. 11 provide a view of one implementation of the propane fueling system within the charging truck, it is to be understood that various embodiments might exist and that the present technology encompasses any such modifications, variations, or equivalent arrangements that are in line with the principles described herein.

[0170] FIG. 12 illustrates central control and management systems 1200 that serve as the operational brain of the autonomous propane-powered charging truck in the inventive mobile electricvehicle (EV) charging system 101. FIG. 12 illustrates how various subsystems within the truck 200 communicate and collaborate to ensure efficient and reliable charging services.

[0171] At the heart of FIG. 12 is the central processor 1210, which acts as the command center of the truck's operations. In at least one embodiment, the central processor 1210 is a high-capacity computational processor which executes the Al-driven algorithms (Al routine) that optimize route navigation and scheduling, processes real-time data from the truck's sensor suite 560, and makes complex operational decisions.

[0172] Interconnected with the central processor 1210 is a navigation subsystem 1220, which utilizes GPS data, machine vision, LIDAR, and other sensor inputs to facilitate accurate and safe vehicle guidance through varying traffic conditions and geographic terrains.

[0173] A vital element depicted in the schematic is an energy management system 1230, which controls the flow of power from the propane generator to both the truck's drive system and the charging apparatus. The energy management system 1230 ensures that the generator operates at optimal efficiency and that energy reserves are properly allocated based on the truck's propulsion needs and the EV charging requirements.

[0174] A safety management module 1240 is responsible for continuously monitoring (and is configured to continuously monitor) the charging truck's operations to identify and respond to any potential safety issues. It interfaces with the truck's various safety mechanisms, such as obstacle detection sensors and emergency shutdown controls, to maintain the highest standard of operational safety.

[0175] A charging control system 1250 manages the electrical connections to the EVs, overseeing the engagement of charging connectors and the transfer of power. This charging control system 1250 works in tandem with the EVs' charging protocols to deliver power safely and efficiently.

[0176] A fleet communication network 1260 shown in the FIG. 12 facilitates the transfer of information between individual trucks 200 and a centralized fleet management server. The fleet communication network 1260 allows for coordinated operations across the fleet, providing updates on vehicle status, location, energy usage, and charging service progress.

[0177] User interfaces and diagnostic consoles 1270 allow operators to input commands, customize settings, monitor system status, and troubleshoot issues when necessary. This human-machine interface is integral for overseeing the autonomous systems and making manual adjustments if required.

[0178] Lastly, an external communication gateway 1280 is where data exchange occurs with external networks, such as traffic management systems, emergency services, and customer service centers. This gateway ensures that the charging truck can operate in harmony with broader smart transportation frameworks.

[0179] FIG. 12 illustrates a systematic approach to the integration of control and management systems within the autonomous charging truck, demonstrating how it balances autonomy with safety, efficiency with reliability, and innovation with user-friendly operation. As with other figures in this application, FIG. 12 illustrates one embodiment of the truck's systems. The technology as described herein comprehensively covers variations and equivalents that enable the same functional utility in delivering an efficient, automated mobile EV charging service.

[0180] FIG. 13 illustrates environmental benefits of the disclosed autonomous mobile EV charging system 101 , showcasing a comparative analysis chart 1300 that elucidates the emissions footprint for the propane-powered charging trucks 200 as described herein relative to traditional grid-powered charging stations. FIG. 13 offers a tangible demonstration of the eco-friendly advantages integral to the invention's use of clean-burning propane rather than conventional, coal-derived grid electricity. For example, such demonstration may be provided to the operator of the system 101.

[0181] The charging truck 200 may comprise (in other words, may be equipped with) with an environmental control system to monitor and reduce emissions associated with the charging operation. For example, the environmental control system may comprise a comparative emissions monitor that displays environmental benefits of using the propane-powered generator compared to traditional coal- powered grid electricity. The left portion of FIG. 13 represents the typical emissions associated with conventional coal-powered electricity sources 1310, which are commonly used to supply power to conventional fixed EV charging stations. Benchmark values for carbon dioxide (CO2), sulfur oxides (SOx), nitrogen oxides (NOx), particulate matter (PM), and other pollutants are depicted with respect to their environmental impacts. Conversely, on the right, the chart 1300 presents the reduced emissions profile for the propane-powered generator units 1320 aboard the autonomous charging trucks. Relative to the coal-based emissions benchmarks, reductions in key pollutants are visually summarized, showcasing the considerably lower levels of CO2, SOx, NOx, and PM emissions produced by propane combustion. Central to the chart is an overlay or 'delta' comparison 1330 that highlights the differential in emissions between the two power sources. This delta comparison underscores the significant reduction in pollutants enabled by the use of propane in the technology as described herein — an environmentally superior alternative as reflected by the chart metrics.

[0182] A legend 1340 provides explanatory notes and specific quantifications forthe pollution metrics portrayed in the chart. These clarifications may include factors such as the typical energy mix of a regional grid, the efficiency of propane combustion in generator units, and the relative impact of these pollution metrics on air quality and climate change.

[0183] Supplementary to the emissions comparison, FIG. 13 also illustrates graphical representation 1350 illustrating potential ancillary benefits such as noise reduction, decreased greenhouse gas (GHG) footprint, and improved local air quality that further bolster the environmental case forthe system’s mobilecharging approach. FIG. 13 illustrates the contribution of the system 101 and technology as described herein to sustainable transportation, highlighting how the mobile propane-powered EV charging trucks can help mitigate the negative ecological effects of fossil fuel dependence in the transport sector. FIG. 13 thereby not only complements the technical disclosures of other figures but also situates the invention within the broader context of environmental stewardship and clean energy initiatives. While FIG. 13 shows an analysis format for comparing emissions, it is to be understood that various other metrics, methods, and presentations that serve to effectively demonstrate the environmental advantages of the technology as described herein may be employed without departing from the inventive concept of the technology as described herein.

[0184] FIG. 14 provides a diagrammatic representation 1400 of the alignment of the autonomous propane-powered charging truck system 101 with anticipated regulations limiting nighttime electric vehicle (EV) charging from the grid. This chart illustrates how the system 101 maintains charging capabilities within the context of such regulations and its adaptability to a regulatory landscape prioritizing sustainable energy practices.

[0185] The diagram 1400 features a timeline or schedule chart 1410 indicating typical periods when grid charging restrictions may apply, such as nighttime hours when solar power is unavailable. These periods are contrasted with the operational timeframe of the mobile charging fleet, which is not bound by these limitations.

[0186] A summary area 1420 of FIG. 14 highlights the unique capability of the autonomous charging trucks 200 to circumvent grid reliance during restricted times, with emphasis on the trucks' use of propane — a cleaner fuel alternative to provide electrical energy for EV charging. This feature is shown as particularly beneficial during periods when traditional stationary charging infrastructure would be impacted by regulatory constraints against grid use.

[0187] Additionally, the chart 1400 illustrates that the Al systems integrated within the trucks provide a dynamic routing and scheduling advantage 1430. These Al systems allow for the adjustment of truck deployment in response to grid regulation shifts, ensuring the fleet can continue to provide uninterrupted charging services regardless of the regulatory environment.

[0188] The visual representation also encompasses a depiction 1440 of the environmental and gridrelief benefits provided by the use of propane as an alternative fuel source, particularly during periods of peak grid demand. This further underscores the synergy between the charging system and the goal of reducing grid strain and supporting broader renewable energy adoption. Narrative elements 1450 as illustrated in FIG. 14 may explain the role of the wireless communication protocols in managing charging operations with EVs and their owners, emphasizing the ability to easily communicate and adapt to changing regulations on when and where charging may occur.

[0189] Overall, FIG. 14 delineates how the autonomous mobile charging system 101 as described herein is configured to operate within and adapt to a regulatory framework that may impose time-based restrictions on EV charging from the grid. By leveraging cleaner propane fuel and sophisticated Al-driven logistics, the charging trucks offer a solution that is not only compliant with such regulations but also enhances grid stability and supports the transition towards more sustainable energy consumption patterns.

[0190] FIG. 14 illustrates one embodiment, and is indicative of the broader functionality and the proactive design approach of the technology as described herein to tackle regulatory considerations. The depicted system showcases a ready adaptation to regulatory changes and the flexibility to support EV charging demand, serving as a model for sustainable and resilient EV charging solutions within modern energy ecosystems.

[0191] FIG. 15 schematically illustrates charging of an electric aircraft 1510 by a charging aircraft 1500, in accordance with various embodiments of the present technology. The electric aircraft 1510 (for example, an electric drone, or another electric aircraft) is an EV as described herein and therefore has components and modules as described herein with reference to the EVs 110. To operate charging of the electric aircraft 1510, the same methods as described herein with reference to the charging of the EVs 110 by trucks 200 may be implemented. For example, the electric aircraft 1510 has the charging port 540, connections 140 with the charging aircraft 1500, and the EV communication unit 930. The charging aircraft 1500 has the same components as the charging truck 200 as described herein. For example, the charging aircraft 1500 has: onboard clean propane-powered generator 120, advanced navigation equipment 130, self-contained power generation unit 210, retractable cabling systems 230, wireless communication transceivers 240, aerodynamically optimized body 250, power generation unit 310, propane storage tanks 320, navigation hardware 330, control and distribution unit 340, wireless communication hardware 360, charging interface 350, connector assembly 410, precision drive system 420, housing and protective casing 430, connection alignment 440, communication modules 450, deployable charging arm 520 and charging connector 530, energy transfer module 580. The energy transfer mechanism in the charging aircraft 1500 operates as described in FIG. 8. The communication protocol is the same as illustrated in FIG. 9 and described herein for the charging truck 200 and the EV 110. In addition, the charging aircraft 1500 has autonomous operation and safety features 1000 as described herein with reference to FIG. 10, and propane fueling system 1100 as illustrated in FIG. 11 for the charging track 200 and described herein, and central control and management systems 1200 as illustrated in FIG. 12 for the charging track 200 and described herein.

[0192] While preferred embodiments have been described above and illustrated in the accompanying drawings, it will be evident to those skilled in the art that modifications may be made without departing from this disclosure. Such modifications are considered as possible variants comprised in the scope of the disclosure.

[0193] In the detailed description, numerous details are set forth in order to provide a thorough understanding of the present invention. It should be clear, however, that the present invention may be practiced without these specific details, which are presented here for the purposes of illustration and explanation. While the description above contains many specificities, these should not be construed as limitations on the scope of the invention, but rather as exemplifications of various embodiments thereof. Many other variations are possible, for instance, different configurations of the autonomous vehicles, variations in the Al algorithms employed for routing optimization, or alterations in the fuel management systems.

[0194] It will be appreciated that the constructions and configurations disclosed herein are exemplary in nature and that these embodiments do not limit the scope of the invention. The present invention is intended to cover all modifications and variations within the scope and spirit of the invention as described herein and as defined by the following claims. Equivalents of the claimed inventions that do not depart from the scope of the patent as defined by the claims are also intended to be covered by this disclosure.

[0195] Moreover, in the description provided, various features may have been grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, inventive aspects may lie in fewer than all features of an individual disclosed embodiment.

[0196] Furthermore, while the invention has been described in terms of several embodiments, it will be evident to those skilled in the art that the invention can be adapted to other uses and applications and that such other uses and applications can be accomplished without departing from the spirit and the scope of the invention. Similarly, the sequence of steps in any method claim below may vary unless specified otherwise in the claims themselves.

[0197] In closing, it is to be understood that the Detailed Description and the Claims are not intended to limit the scope of the disclosure to the precise forms and embodiments disclosed herein. Rather, they are intended to include all such forms and embodiments that are evident to one skilled in the art and that come within the scope of the disclosure and the appended claims.

Claims

CLAIMS:1 . An autonomous mobile electric vehicle charging system for charging electric vehicles, the system comprising: a fleet of charging trucks autonomous from each other, each charging truck being equipped with an onboard propane-powered generator; an autonomous navigation system configured to guide the charging trucks to the electric vehicles ; a wireless communication interface configured to initiate charging sessions between the charging trucks and the electric vehicles; and an artificial intelligence module configured to optimize routes and scheduling of the charging trucks based on demand and traffic conditions.

2. The system of claim 1 , wherein the pro pane- powered generator is also configured to power the charging truck while providing electricity for EV charging.

3. The system of claim 1 or 2, further comprising: a charging interface mechanism adapted for establishing a connection with the EVs to provide in-motion charging capabilities.

4. The system of any one of claims 1 to 3, wherein the autonomous navigation system comprises sensors located on the charging trucks and configured to collect data in real time from an environment surrounding the charging trucks.

5. The system of any one of claims 1 to 4, wherein the wireless communication interface uses secure protocols to authenticate the electric vehicles before commencing charging sessions.

6. An autonomous mobile electric vehicle charging truck comprising: a propane fuel storage system; a propane power generation unit connected to the propane fuel storage system; an autonomous navigation control module configured to receive and interpret data from autonomous driving sensors for autonomous vehicle operation; a control and distribution unit configured to regulate electricity flow from a generator to the electric vehicle; an interface mechanism configured to facilitate energy transfer to an EV; and a communication module configured to initiate and to control an automated charging session.

7. The autonomous mobile electric vehicle charging truck of claim 6, further comprising a safety management module configured to continuously monitor operation of the autonomous mobile electric vehicle charging truck to identify and to respond to a safety issue.

8. A method for charging electric vehicles using an autonomous mobile charging truck, the method comprising: navigating the charging truck to an electric vehicle based on Al-optimized routes; autonomously establishing a charging connection with the electric vehicle; managing and controlling a flow of electricity from a propane-powered generator to the electric vehicle; wirelessly communicating between the electric vehicle and the charging truck to synchronize and control the charging session.

9. The method of claim 8, wherein the charging truck provides charging services to the electric vehicle while both the charging truck and the electric vehicle are in motion.

10. The method of claim 8 or 9, wherein the Al-optimized routes are generated by an Al routine which is configured to adjust truck routes in real time in response to traffic conditions and demand distribution.11 . A system for providing mobile electric vehicle charging services, wherein the system is configured to use propane as a fuel source for generating electricity required for charging the EVs.

12. The system of claim 11 , wherein the system is configured to generate adaptive scheduling that allows the charging trucks to deploy pre-emptively based on predicted demand patterns identified through Al analysis.

13. A mobile electrical vehicle charging truck configured to interface safely with electric vehicles and provide in-motion charging, wherein the truck is equipped with an environmental control system to monitor and reduce emissions associated with the charging operation.

14. The mobile electrical vehicle charging truck of claim 13, wherein the environmental control system comprises a comparative emissions monitor that displays environmental benefits of using the propane-powered generator compared to traditional coal-powered grid electricity.

15. A method for managing a fleet of autonomous mobile electrical vehicle charging trucks, wherein the method uses a centralized control system to coordinate truck deployment, energy management, and wireless communication protocols for charging electrical vehicles in compliance with anticipated energy regulatory measures.

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