GB2605834A

GB2605834A - System for charging electric vehicles (EVs) and related methods

Info

Publication number: GB2605834A
Application number: GB2105416.8A
Authority: GB
Inventors: William Cowper Stephen
Original assignee: Individual
Current assignee: Individual
Priority date: 2021-04-15
Filing date: 2021-04-15
Publication date: 2022-10-19
Also published as: WO2022219362A1; GB202317436D0; GB202105416D0; GB2621739A

Abstract

There is disclosed a computer-based system for managing energy supply and demand at an electric vehicle (EV) charging facility, which charging facility may comprise a plurality of EV charge points. The system comprises a data capture module 20 configured to receive data representative of a number of EVs, including their charge status and location. An energy supply and demand processing unit 30 determines a subgroup of the EVs and corresponding prospective customers based on said received data. An offer module 40 is configured to issue EV charge offers for the benefit of the EV customers in the subgroup. These EV charge offers each include at least a proposed EV charge time and may also include an allocated EV charge point. In this way, not only utilisation of the EV charging facility may be optimised but customer demand and EV autonomy are advantageously managed. The system may define a geographic region 102 using an isochrone 101.

Description

System for Charging Electric Vehicles (EVs) and Related Methods

Technical Field

The present application relates to a system for managing energy supply and customer demand in connection with an EV charging facility, such as an EV charging facility comprising one or more EV charge points. The present application also covers related computer applications, such as applets for smartphones, methods and computer-readable media or computer products containing related readable instructions.

Background

In 2020, over 10% of all new cars sold in the UK were plug enabled Electric Vehicles (EVs), either fully electric or plug-in hybrid vehicles. This is an increase from a 2.5% share in 2018, and the market share for EVs is increasing rapidly as new models become available.

Currently, it is estimated that around 455,000 EVs operate in the UK. The UK Government announced in November of 2020, that from 2030, the sale of new petrol and diesel-powered cars and vans would be discontinued. It is expected that this will drive the percentage of EVs amongst new vehicle sales up significantly, over the coming years. A similar pattern is expected globally, as an increasing number of governments and automakers commit to EVs.

According to recent studies, there are circa 40,000 public charge points in the UK, of which less than 10,000 are classed as 'Rapid' or 'Superchargers', i.e. as being capable of charging an EV from 20% to 80% capacity in a period as low as 18 minutes, but typically around 45 to minutes, depending on the vehicle and the kW rating of the charge point.

A very high proportion of current EV owners have private off-street parking and home charging solutions. The typical range of an EV on a single charge has increased significantly in the recent few years, from less than 100 miles to over 300 miles. However, these ranges are still impacted by, for example, cold weather which can significantly reduce actual driving range.

While EV ownership is currently the exception and EV owners have largely tended to have either overnight charging facilities via off-street parking at home (the UK Government has, for example, sponsored over 140,000 home charging installations via a range of incentive schemes) or to use the circa 9,000 charging facilities provided at their places of work, this model is clearly not going to work as the proportion of EV owners increases and EVs become the most common vehicles on the road, especially in relation to the introduction of electrically powered commercial vehicles, such as vans. With the proportion of private off-street parking being lower in towns and cities, the challenges of EV owners who live in apartments and other shared spaces will accelerate the issue of a growing stress on the existing home or office charging network. This will drive reliance upon public charging infrastructure.

Unlike traditional fossil-fuel serving filling stations, where typical stop times are between 2 to 5 minutes, visiting even a 'Rapid' or 'Supercharging charging station demands longer stops. Recent data reported that 63% of UK-based users of Rapid charge stations typically charged their EVs for between 20 to 50 minutes at a time. As more EVs come onto the roads which don't have the ability to charge overnight or at their workplace, public EV charging infrastructure will be in higher demand. These extended charging times have thus the potential to generate significant queuing and congestion. The notorious EV 'range anxiety', where the concern has traditionally been whether the EV would have sufficient range to get to the next charging point or destination, will be replaced by EV 'journey time anxiety', where the amount of time required taken to obtain charge at a public charging facility would be variable and difficult to predict or even estimate. This may have a significant impact on business and personal life, and thus there is a need to improve the management of public EV charging facilities.

Statement of Invention

The present application sets forth an intelligent solution which, in essence, shifts public EV forecourts from being simply 'passive' sites that respond to incoming EVs and provide no certainty around vehicle dwell times, into being 'active', i.e. 'aware', of potential customer demand around their locations. As a consequence, EV charging facilities will be able to actively manage, and even incentivise, EV customers to use their charge points while providing some certainty of dwell time for recharging, thus mitigating journey time anxiety.

Accordingly, the present disclosure sets forth a system for managing energy supply and customer demand in connection with at least one EV charging facility. The system may comprise an EV data capture module. The data capture module may be configured to receive data representative of at least a) EV charge status and b) EV location. The system may also comprise an energy supply and customer demand processing unit programmed to elaborate energy supply at the EV charging facility and customer demand based on said received data.

In addition, the system may comprise an EV charge offer module, the EV charge offer module being configured to issue EV charge offers based on said elaborations of the energy supply and customer demand processing unit. Said EV charge offers may each include at least a proposed EV charge time at the EV charging facility, but one or more EV charge points may also be specified in said EV charge offers.

Recent technical advances in Connected Vehicles have made it possible to know the current battery state of an EV, either via an OEM proprietary Application Programming Interface (API) with suitable permissions or by installing an aftermarket telematics device -the type of 'black box' commonly used in Telematics Insurance -but with EV-specific parameters being returned, which may include items such as battery charge %, charge state, type of charger being used, etc.. Accordingly, the EV data capture module may be configured to receive any of such data.

By utilising this information, the system may be configured to use the location of a given charging facility or forecourt and create a geofence' area around that location in 'real time' 15 which may comprise one or more of: - a simple radius around the site; - a series of polygons defined by specific roads; and - an isochrone, which may take advantage of real time traffic flow data to create, for example, a 5-minute drive map from the EV charging facility boundary, based upon current journey durations.

The system may be configured to check the battery status of all known vehicles within this boundary as well as, as a further option, to confirm whether they were heading in the general direction of the location of the EV charging facility, as it seems unlikely that customers would be willing to go back on themselves during a planned journey. However, this factor may be parameterised and may thus be the subject of a user-defined option. This parameter or option could be added to the data received by the data capture module.

By the same token, if the battery charge level is for example over 70%, it is unlikely that the owner will be wanting to charge, but a vehicle with a charge level of less than, for example, 20% would be a more likely candidate; again, this factor may be parameterised and may accordingly be the subject of a user-defined option -or it could alternatively be a system defined option.

All EVs that match preselected criteria of battery level and, as an option, journey direction may be made by the system automatically the subject (i.e. the addressees) of one or more offers to visit the EV charging facility for charging. This may happen, for example, via: - a push message sent directly to a customer's mobile phone; - a notification notified by an app which was downloaded on the customer's mobile phone; - directly, on a display or audio device of the EV, if this is supported; and/or, -some other offer communication means, whilst minimising risk of distraction to the driver.

This invitation may be incentivised by the EV charging facility operator using common means such as percentage discount on retail purchases, lower price per kWh for charging or any other means of incentive.

In some implementations, the offer or invitation may also include a 'reserved time interval or slot within which the customer is invited to commence a recharge operation.

In some implementations, the offer or invitation may include a particular charge point (which may be one out of a plurality of charge points present in the EV charging facility) which is suitable, or particularly suitable, for that electric vehicle.

With a system as described herein, the concept may be similar to that of a restaurant table reservation, with reservations being time limited.

By knowing the charge level of the battery and the vehicle type (for example via a vehicle identifier also provided to the data capture module) prior to charging commencing, and optionally also a preferred or desired destination, the system may be able to accurately estimate the 'dwell time' required for each vehicle. Accordingly, the system may be able to provide improved certainty for a customer as to how long the vehicle will be stopping at the charging location for recharge.

The driver/customer may be provided with the opportunity to confirm that they would like to accept the offer. This may in turn reserve a particular slot for a given period of time, ensuring that when they arrive at the site, they may drive straight into the charge point and be on their way according to a minimum stop time for recharge.

Any reserved slots may be indicated at the EV charging facility and/or at each EV charge point within the facility as being 'reserved' -meaning that they may not be available to other users for that period of time with the option of a visible indication of reservation as well as an option to electronically 'lock' the charger until the reserved vehicle is in position. This may also include a visible indication of how long the charging is estimated to take, based on knowing, or on an estimate of, the starting capacity of the vehicle when charging commences and the measurement of, or an estimate of, the actual amount of energy being delivered to the vehicle once connected and charging along with the desired battery percentage charge level that the user desires. This may in addition allow casual users of the EV charging facility to make informed decisions about which charge point to wait at, if all charge points are full when they arrive.

Adequate management of available charging slots may form an important part of the solution, as this may allow the facility operator to manage and forecast their energy demand.

Accordingly, in periods of low activity, the size of the isochrone may be increased, or the incentives may be increased, for example to broaden the scope of candidate vehicles.

In busy periods, the isochrone may be reduced, or the incentives may be reduced, eliminated, or reversed (i.e. a premium would have to be paid) to minimise any surplus demand at that EV charging station.

In a situation where an operator has a network of EV charging stations, methods as described herein may be used to encourage the smoothing out of charging demand across nearby charging stations, thus avoiding delays for the drivers and providing better utilisation of the station's charge facilities.

By integrating methods as described herein with route planning applications and other apps, it may be possible for EV drivers to indicate an intention to pre-book a charging slot when planning a route. Accordingly, in some implementations the system may take care of the actual timing of reserved slot based upon the actual location of the vehicle on the journey.

The use of affiliations of the drivers to member clubs or similar loyalty and/or privilege 30 schemes, may also be used by the EV station operator as an automated means of payment for the charging -thus avoiding the requirement for payment cards or other means of payment at the charging station.

Over time, the data collected by the system may allow artificial intelligence (Al) or machine learning tools to better predict variables such as: the likelihood of a customer to accept an offer of a reserved slot based on a given amount of charge in the battery, time of day, day of week, etc.; the actual dwell time of a given user, as some may prefer to charge up to the 80% level, whereas others may just add a smaller amount of energy at a time (this in turn would allow improvement in the accuracy of the estimation of the duration of the offered or reserved slot); and, levels of demand at a specific EV charging station -allowing better management of energy resources between renewable energy stored on site, and energy pulled directly from the grid.

Station operators may use the data to model the location and charging point composition of new potential forecourt sites, to understand the potential utilisation at each site and to uncover the areas where there are gaps in the charging infrastructure network that need filling.

According to an aspect of the present disclosure, there is provide a system for managing energy supply and demand at an EV charging facility, the system comprising: a data capture module configured to receive data representative of: a) a plurality of EVs corresponding to a plurality of respective customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations and d) energy supply availability at the EV charging facility; an energy supply and demand processing unit programmed to determine a subgroup of said plurality of EVs corresponding to prospective customers, based on said received data; and, an EV charge offer module, the EV charge offer module being configured to issue EV charge offers to said prospective customers subgroup, wherein said EV charge offers each include at least a proposed EV charging time at the EV charging facility.

The data capture module may be configured to further receive reservation confirmations of one or more of said EV charge offers.

These reservation confirmations may be automatically generated, or may be customer generated, that is generated pursuant to a specific command issued by the customer.

The data capture module may be configured to further receive customer generated reservation requests, in other words proposals for one or more reservations that are specified by one or more commands generated by the customer, for example via the applet or website described herein.

The energy supply and demand processing unit may be further programmed to reserve one or more EV charging points provided at the EV charging facility based on said reservation confirmations or requests.

The data capture module may be configured to further receive data representative of e) EV journey, wherein said EV journey data may comprise data representative of any one or more of: a battery charging state; a power input, such as an instant or average power input; a power output, such as an instant or average power output; a remaining driving range; a direction, such as a direction relative to the EV charging facility; a speed, such as an instant or average speed; and an identifier of either the EVs, such as a Vehicle Identification Number, or of a telematics device attached to the EVs.

The above identifier may alternatively be used as the basis for said data representing the EVs and corresponding customers.

The energy supply and demand processing unit may be programmed to include any one or more of the EVs and corresponding customers in said subgroup: if the EV locations of said one or more EVs are within a geographical region disposed around the EV charging facility; and/or, if the EV charge levels of said one or more EVs are below an upper charge level threshold and/or above a lower charge level threshold.

The energy supply and demand processing unit may be further programmed to define said geographical region by one or more of: a radial distance from the EV charging facility; one or more lines defined by one or more respective roads and, an isochrone relative to the EV charging facility; and/or, wherein the energy supply and demand processing unit is further programmed to define said upper and lower charge level thresholds.

The energy supply and demand processing unit may be further programmed to adapt said geographical region and/or said upper and lower charge level thresholds to the data received by the data capture module.

The energy supply and demand processing unit may be programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said reservation confirmations.

The energy supply and demand processing unit may be programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said user generated reservation requests.

The energy supply and demand processing unit may be programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said reservations of the one or more EV charging points provided at the EV charging facility.

The proposed EV charge time may comprise a proposed EV charge time or time interval within which an EV charge operation is to be started and/or completed.

The EV charge offers may comprise one or more allocated EV charge offers that specify one or more EV charge points provided at the EV charging facility.

The EV charge offers may comprise one or more incentivised EV charge offers that specify at least one incentive for the customer to accept said incentivised EV charge offers.

According to a further aspect of the present disclosure, there is provided a computer application (hereinafter "app"), such as an applet for a smartphone, for communicating with a system according to the previous aspect of the present disclosure, the app being configured: to send to the data capture module data representative of an EV corresponding to a respective customer of the EV charging facility, EV charge level and EV location; and, to receive from the EV charge offer module one or more EV charge offers.

The app may be further configured: to generate one or more reservation confirmations for sending to the data capture module.

Such reservation confirmation may be automatically generated upon, for example, receiving one or more EV charge offers, or may be user generated, as described herein.

The app may be further configured: to generate one or more user generated reservation requests for sending to the data capture module, as described herein.

The app may be further configured: to output to the prospective customer the one or more received EV charge offers and/or reservations of the one or more EV charging points at the EV charging facility based on said one or more received EV charge offers.

According to a further aspect of the present disclosure, there is provided an EV charging facility comprising a system according to one of the previous aspects of the present disclosure.

According to a further aspect of the present disclosure, there is provided a network comprising two or more EV charging facilities, the network comprising a system according to one of the previous aspects of the present disclosure, wherein the data capture module is configured to receive data representative of energy availability at the two or more EV charging facilities and wherein said EV charge offers issued by the EV charge offer module each further include at least a proposed EV charging facility of the two or more EV charging facilities.

According to a further aspect of the present disclosure, there is provided a method of managing energy supply and demand at an EV charging facility, the method comprising: receiving data representative of: a) a plurality of EVs corresponding to a plurality of respective customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations; and, d) energy supply availability at the EV charging facility; determining a subgroup of said plurality of EVs comprising prospective customers based on said received data; and, issuing EV charge offers to said prospective customers subgroup, wherein said charge offers each include at least a proposed EV charge time at the EV charging facility.

The method may further comprise: receiving reservation confirmations based on said EV charge offers, which can optionally be user generated reservation confirmations, as described herein, or user generated reservation requests, as also described herein; and, reserving one or more EV charge points provided at the EV charging facility based on said reservation confirmations and/or reservation requests.

According to a further aspect of the present disclosure, there is provided a method of managing energy supply and demand at a network of two or more EV charging facilities, the method comprising: receiving data representative of: a) a plurality of EVs corresponding to a plurality of respective potential customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations-and, d) energy supply availability at each of the two or more EV charging facility; determining a subgroup of said plurality of EVs comprising prospective customers based on said received data; and, issuing EV charge offers to said prospective customers subgroup, wherein said EV charge offers each include at least a proposed EV charge time relating to at least one of the two or more EV charging facilities.

According to a further aspect of the present disclosure, there is provided a computer readable medium or product comprising instructions for performing a method according to any of the corresponding previous aspects of the present disclosure.

Drawings Illustrative implementations will now be described, by way of example only, with reference to the drawings.

In the drawings: Figure 1 is a schematic representation of a system as described herein; Figure 2 schematically represents principles relating to selection of EVs for issuance of EV charge offers, as implemented by the system of Figure 1; Figure 3 schematically represents typical data sent to the system of Figure 1 by an EV or a user thereof; Figure 4 exemplifies a status display at an EV charging facility, showing information in relation to 12 EV charging points; and Figure 5 is a flow chart illustrating a process of issuing one or more EV charge offers, as described herein.

Throughout the description and the drawings, like reference numerals refer to like features.

Detailed description

Figure 1 schematically illustrates a system 100 for managing energy supply and demand at an EV charging facility 3. A sample EV charging facility 3 is schematically shown in Figure 2 and will not be described in detail herein. However, it will be understood that electric vehicles 1 On short, "EVs") of the kind shown in Figure 1 are able to stop at the EV charging facility 3 to obtain charge to be stored in their respective batteries (also not shown herein) -whether such EVs 1 are fully or only partially electrically operated.

The system 100 may as an option manage a number of members in connection with, for example, a 'Member Club', wherein the members are members of the Member Club by virtue of a subscription (which can be free or paid for) that results into membership of the Member Club. For the purposes of the present description, the members own and/or drive EVs 1 and, as such, will need, from time to time, to recharge the EVs 1. It will be understood, therefore, that the members described herein represent, more generally, a group of users of EVs 1, and therefore a group of potential customers for the EV charging facility 3.

The system 100 described herein has authority to access vehicle data as well as EV charging facility data related to energy supply available at the EV charging facility 3. The vehicle data can be transmitted to the system 100, for example, via a suitable applet for smartphones configured to communicate with the system 100, but this example is not exhaustive. An alternative implementation could be, for example, via a web browser, over the internet, for example through a dedicated website. It will also be appreciated that corresponding web applications or customer applets could alternatively be integrated into other solutions provided by partners of the Member Club such as 'forecourt providers', i.e. owners of EV charging facilities 3, EV leasing companies, public or private employers or crowdsourced charging information applets etc.. The applet or website could be responsible for managing user/customer preferences including any preferences around receiving EV charge offers 41 at the EV charging facility 3, and any incentives related thereto etc.. Two EV charge offers 41 are shown in Figure 2, and the process of issuance of these EV charge offers 41 will now be described.

With continued reference to Figure 1, the system 100 comprises a data capture module 20. The data capture module 20 is configured to receive (and may store) data from the EVs 1 participating in the Member Club, directly or optionally via secure Cloud connectivity 2, as shown in Figure 1. The data could be delivered 'over the air' using either: - the fitting of telematics devices to each EV 1 within the Member Club, as part of their membership; or, -connection to their vehicle via an Application Programming Interface ("API") of the EV vehicle manufacturer, with permission for this access being granted as part of the membership and utilising, for example, an inbuilt telematics SIM in the vehicle, but other methods would be possible and apparent to the skilled person.

The data received by the data capture module 20 may include EV vehicle data such as: - an instantaneous or average battery charge level 21 (which can be expressed as a percentage or "%"); note that this level would be available both when the EV 1 is driving or charging at the EV charging facility 3; - a battery charging state (indicating whether the battery is charging o not charging); -a type of charger connected (this may include connector type and charge rate); - an instantaneous or average energy and/or power in input or output from the EV 1; - an estimated remaining driving range (for example, expressed in miles); - an EV Location 22 (for example, expressed in longitudinal and latitudinal coordinates, or according to another reference system) -a direction or 'heading' 24 of the EV 1 (such as an instantaneous direction expressed according to the cardinal reference system); - a speed of the EV 1, such as an average or instantaneous speed (for example, expressed in miles per hour); - an identifier of either the vehicle, such as a Vehicle Identification Number (VIN) or the telematics device if fitted, which would then be linked to the vehicle in backend databases operably connected to the system 100.

Figure 3 summarises a possible set of vehicle data that may be exchanged with the system 100 of Figure 1, via the data capture module 20. In addition, the system 100 is provided in connection with at least one EV charging facility or 'forecourt' 3. Accordingly, the data capture module 20 also receives data pertaining to a supply of energy available at the EV charging facility 3. This information can comprise a number of available EV charging points Sat the EV charging facility 3. Figure 4 shows, for example, the number of available EV charging points 5 at the EV charging facility 3 at a given time instant during the day. The information can comprise charging rates available at the EV charging points 5 (it should be noted that it is a possibility that different EV charging points 5 may recharge EVs 1 according to different charging rates), the total amount of energy being instantaneously or on average supplied by the EV charging facility 3 and the type of energy being so supplied (for example, whether derived by fossil fuels of renewable).

With continued reference to Figure 1, the system 100 further comprises an EV charge offer module 40 capable of issuing EV charge offers 41 to possible, i.e. potential, customers/drivers.

These EV charge offers 41 can be routed to the EVs 1 via the Cloud 2, as shown in Figure 1. However, other modes of delivery are possible. Importantly, these EV charge offers 41 are issued by the EV charge offer module 40 after an energy supply and demand processing unit 30 which is also part of the system 100 has determined a subgroup of EVs 1 suitable for receiving such EV charge offers 41, based on estimated customer demand versus availability of energy at the EV charging facility 3. Accordingly, the system 100 is capable of managing the energy supplied by the EV charging facility 3 across multiple EV charging points 5, and, if needed, across a network two or more EV charging facilities 3, for example EV charging facilities 3 owned by a same EV forecourt operator.

It can be said that the system 100 of Figure 1 is thus able to manage the availability of all EV charging points 5 provided in the EV charging facility 3 in 'real time'. Accordingly, the system 100 may be initially configured to scan a region 102 geographically located near and/or around the EV charging facility 3 for qualifying members of the Member Club and identify suitable candidates for receiving EV charge offers 41 comprising a time-limited, i.e. 'reserved', slot for charging the EVs 15. This is schematically shown in Figure 2. The issuance of one or more EV charge offers 41 can potentially happen in combination with tailored incentives to accept the slot, such as a discount on the charge received by the EV during recharge, or the purchase of food in a shop located at the EV charging facility 3.

The acceptance of the EV charge offers 41 issued by the EV charge offer module 40 may also be managed by the system 100. This can be done via a dedicated reservation processing unit. However, the function of the reservation processing unit could alternatively be performed, for example, by the energy supply and demand processing unit 30, or by the EV charge offer module 40-if this a dedicated component of the system 100 is less preferred. Accordingly, the energy supply and demand processing unit 30 or the EV charge offer module 40 may in addition control access of the EVs 1 to the EV charging slots 5 provided at the EV charging facility 3 by reserving 'slots' (i.e. time intervals) for any EVs 1 that have accepted an offer of charging, for example within a controlled timeframe "X" as shown in Figure 5. Alternatively, these offers 41 could be automatically accepted by the Member Club website or applet, based on customer preference or any default settings.

An important feature of the system 100 can be described in connection with Figure 2. The system 100 may be configured to control the geographical extent of an area 102 disposed near and around the EV charging facility 3 within which potential candidate EVs 1 for an offer of charging 41 are selected based upon the current levels of demand at the particular EV charging facility 3. To this purpose, the data capture module 20 is informed at least of EV charge level and EV vehicle location in connection with an initial geographical area considered 'of interest' to the EV charging facility 3, that is an area with the deemed presence of possible EVs 1 with corresponding EV customers. Among various possibilities for actively performing such control are those of: reducing or increasing a radius distance from the EV charging facility; identifying boundary roads which delimit said geographical area 102; and, varying an estimated time of arrival 23 of the EVs 1 according to an Isochrone' 101 -in other words, selecting a region 102 within which estimated times of arrival 23 of the EVs are below a set threshold. Note that the time of arrival 23 could be based on an estimation provided by the EV 1, or it could alternatively or additionally be estimated by the processing unit 30 based upon relevant data received by the data capture module 20. This geographical region 102 can be adapted by the energy supply and demand processing unit 30 of the system 100 based on the data received by the data capture module 20. The system 100 may obtain estimated driving times to the EV charging facility 3 from the EVs 1, alongside the other data, or the processing unit 30 may estimate such parameters independently based upon one or more suitable models. These models however do not form part of the present application and are therefore not further described herein.

In multi-site operations, the system 100 described herein may allow the operator of a network comprising two or more EV charging facilities 3 to balance demand by increasing or decreasing the volume and level of incentives offered at a given EV charging facility 3 to encourage EVs 1 to charge at another nearby site with perhaps lower utilisation or an abundance of stored energy, at times of high grid pricing.

The system 100 may in addition provide visibility of the reservation status of its EV charging points 5 at the entrance of the site or at the individual EV charging points 5 on one or more displays or visual boards 4, with optional estimates of when the EV charge points 5 will next become available for general usage. This is shown in Figure 4.

The system 100 may in addition be able to manage future reservations based upon proposed journey details, with any actual reservation slots being managed in 'real time' using EV charge level 21 and EV location 22 information obtained during the actual journey. This and other methods of using the system of Figure 1 will now be described in connection with the flowchart shown in Figure 5.

With reference to Figure 5, there are illustrated methods of using the system 100 of Figure 1.

The system 100 requires information on energy supply availability at the EV charging facility 3 of interest. In Figure 5, the system 100 initially determines 110 the status of each EV charge point 5 provided at the EV charge facility 3. If an EV charge point 5 is available 111, then the system 100 proceeds with gathering information relating to energy utilisation at the EV charging facility 3. This is shown by step 112 shown in Figure 5.

If energy use at the EV charge facility 3 is normal 115, then the system 100 scans for EVs 1 within a geographical area 102 such as the one shown in Figure 2. In Figure 2, the geographical area 102 of interest is within isochrone 101, with an estimated time of arrival threshold set for nearby EVs 1 at below 6 minutes. These values are of course only indicative, and many different alternatives would be possible.

If the energy use at the EV charge facility 3 is high, then this means that energy availability is low, because the EV charging facility 3 is already being used close to capacity by EVs undergoing recharge operations. In this case, the system 100 decreases 113 the extent of the geographical area 102 shown in Figure 2 by adopting a more conservative isochrone 101 which will thus delimit an area 102 of less geographical extent compared to the scenario with energy use normal.

If the energy use at the EV charge facility 3 is low, then this means that energy availability is high, because the EV charging facility 3 is being used far from its capacity by any EVs undergoing recharge operations. In this case, the system 100 increases 114 the extent of the geographical area 102 shown in Figure 2 by adopting a wider isochrone 101 which will thus delimit an area 102 of wider geographical extent compared to the scenario with energy use normal.

Once an appropriate geographical area 102 has been set, the system 100 receives EV charge level 21 and EV location 22 information from the EVs 1 in the geographical area 102, as described above. It is at this stage, that the energy supply and demand processing unit 30 evaluates demand, by identifying 116 one or more EVs 1 that match any relevant criteria for EV charge offer issuance. These criteria may comprise EV charge level 21 within set upper and lower boundaries. Other criteria are however possible, such as EV direction 24 (as shown in Figure 2) compatible with the location of the EV charging facility 3: for example, the system may decide to exclude from offer issuance any EVs 1 not heading in the direction of the EV charging facility 3.

Once a pool of potential, i.e. candidate, EVs 1 have been identified for offer issuance, this information is passed by the energy supply and demand processing unit 30 to the EV charge offer module 40, which will accordingly generate one or more EV charge offers 41 to the appropriate EVs 1, as also shown in Figure 2. This is represented in Figure 5 by step 117.

At this point, any EV charge offers 41 may be automatically accepted by the above-mentioned applet or website. Alternatively, any such EV charge offers 41 may be simply displayed or otherwise outputted to the customers for further evaluation and then acceptance (or rejection) -also via said applet or website, as an example. The system 100 is configured to take into account this degree of EV charge offer acceptance 118 (for example, this step too may be carried out by the EV charge offer module 40). Offers that are not accepted will trigger the issuance of one or more further offers according to step 117 to any incoming EVs into the geographical area 102 of interest. It will be appreciated that the number of acceptances in the flow chart of Figure 5 effectively triggers the issuance of new offers 117 to alternative candidates matching the relevant criteria. However, in alternative implementations of the method, this may trigger a redefinition of the geographical area of interest 102, pursuant to steps 110, 111, 112, 113, 114, 115, 116 and, finally, 117 -as the system 100 pursues maximum utilisation and therefore always tries matching suitable EVs to any available EV charge points 5.

Once any EV charge offers 41 are accepted, the system 100 proceeds with actually reserving 119 time slots at one or more EV charge points 5 at the EV charging facility 3 accordingly.

The system 100 finally checks 120 for arrival of the EVs 1 within the offered time slots. If this condition is satisfied, then the system 100 proceeds with registering the charging sessions and updating the customer accounts 122. In case of no show', then the system 100 releases 121 the bookings or reservations. Again, the release 121 of any bookings or reservations in the method illustrated in Figure 5 triggers the listing 116 of matching EVs 1 present in the given geographical area of interest 102; in other words, the system 100 checks for any further EVs that have entered the area 102. However, in alternative implementations of the method shown in Figure 5, this may trigger a redefinition of the geographical area of interest 102, pursuant to steps 110, 111, 112, 113, 114, 115 and 116-as the system 100always pursues maximum utilisation and therefore always tries matching suitable EVs 1 to any available EV charge points 5.

Two use examples of the system 100 described herein will now be described: Example 1: General use of the system 100 with 'adaptive' EV charge offers 41 An EV customer, who drives an EV 1 with a range of 300 miles is an active member of the Member Club described herein, begins their journey with an initial charge level 21 of EV 1 of 40%. After driving to an appointment 80 miles away, the EV 1 has a charge level 21 less than 20% and has insufficient charge to return to their starting point. Their route back takes them within distance 22 of a geofenced' area 102 of an EV charge facility 3, partner of the Member Club, whose system 100 recognises that the EV 1 is within their catchment area 102 and that the charge level 21 is low. This may automatically trigger a provisional reservation request for the EV 1 which is delivered to the customer via, for example, a push message into their phone which is connected via a screen mirroring application to a screen provided in the EV 1. The customer and driver of the EV 1 sees an EV charge offer 41 for charging the EV 1 and may accept it using a simple voice command which confirms the provisional reservation on the system 100. A charge point 5 is assigned, as part of the EV charge offer 41, and the system 100 may in addition also estimate a time of arrival 23 of the vehicle 1, taking into account the prevailing traffic conditions. Alternatively, the time of arrival 23 may have been estimated by the EV 1, and communicated to the system 100 by the EV 1 itself. This information may be used by the system 100 and in any case it may be reflected in the EV charge offer 41. In other words, the EV charge offer 41 may already specify a suitable time for charging the vehicle at the time of making the EV charge offer 1 Otherwise, this suitable time may be specified at the time of making the actual reservation, after the EV charge offer 41 has been automatically accepted or has been accepted following a user-generated confirmation. This can be as soon as the vehicle arrives at the EV charge facility 3, if there is immediate availability of a suitable charge point 5, or can be after some waiting time. The system 100 would ensure that any waiting time is kept to a minimum, for maximum efficiency of use of the space at the EV charging facility 3. The specific charge point (for example, Point 7) is communicated to the driver by the same communication means as the original offer and is now considered to be confirmed. This communication may in addition include the location of the charging station 3 for use in the EV's navigation system. At the forecourt 3, the status of this particular charging point (Point 7) is now changed to Reserved' and the point is optionally electronically locked to prevent any other users attempting to access it. When the customer/driver arrives at the forecourt 3, they see a display board 4 which indicates that Point 7 is reserved and they drive up to the charge point 5 and can immediately begin charging. When their vehicle 1 is sufficiently charged, they continue their journey.

Example 2: Pre-booking of charging in advance In this use case, the driver is planning a round trip journey of 320 miles with an overnight stay with no opportunity to charge during the night in a vehicle with a range of 300 miles, meaning that they will need to charge at some point on their return journey to be able to return to their final destination. Using an applet which has visibility of charging infrastructure, the driver plans a route to their overnight location with return departure planned for around 3pm. The driver notices that there are several charging forecourts 3 on their return journey route who are partnered with the Member Club. The driver selects one of these forecourts 3 that is approximately one-hour drive away from their overnight stop and makes a request for a booking at 4pm on the following day. The system 100 creates a pre-requested reservation at 4pm on the desired day, at the selected forecourt 3. This class of reservation acts as a prompt to the forecourt's management system 100 to look out for the vehicle 1 entering their geofenced area 102 in a given window around that time and to create an EV charge offer 41 at the appropriate time, which results into a prioritised reservation for the vehicle which is automatically accepted. After their overnight stop, the driver is delayed and doesn't leave until 5pm and traffic is heavier than they had originally planned which means that they do not get into the vicinity of their chosen EV charge facility 3 at the original time. However the management system 100 is sufficiently aware of this from the vehicle position 22 to be able to dynamically i.e. adaptively, alter the existing reservation and to offer a new reservation at 6:30pm, when the vehicle is only a few minutes away from the chosen site 3. The charge point 5 (in this case, for example Point 3) is communicated to the driver and they drive straight to the charge point 5 and begin charging, despite the forecourt having all of its other charge points 5 in use, as it was a peak time for vehicles 1 being charged.

These two examples demonstrate the way that the system 100 described herein and the related methods may have significant impact on the experience of driving an EV 1. There is an elimination of delays due to waiting for charging points 5 to become free and journey times can be calculated with far greater certainty as the charging variables are stress-free.

The above detailed description describes a variety of exemplary systems and of related methods of using such systems for managing energy supply and demand at an EV charging facility. However, the described arrangements and methods are merely exemplary, and it will be appreciated by a person skilled in the art that various modifications can be made without departing from the scope of the appended claims. Some of these modifications will now be briefly described; however, this list of modifications is not to be considered as exhaustive, and other modifications will be apparent to a person skilled in the art.

In the above description, the term "system" has been used in connection with a computer arrangement comprising a data capture module 20, an energy supply and demand processing unit 30 and an EV charge offer module 40. It will be understood that such modules and unit may all be part of a same computer, or system of computers. Accordingly, these modules and unit may not correspond to an equal number of dedicated computer or machines. Such modules and unit are described herein purely in relation to their logical function and role within the system 100. Accordingly, the flow of data between these components of the system will also depend on the actual implementation of these components, bearing in mind that it is a possibility that these components may be part of the same computer or computerised system.

While various specific combinations of components and method steps have been described, these are merely examples. Components and method steps may be combined in any suitable arrangement or combination. Components and method steps may also be omitted to leave any suitable combination of components or method steps.

The described methods may be implemented using computer executable instructions. A computer program product or computer readable medium may comprise or store the computer executable instructions. The computer program product or computer readable medium may comprise a hard disk drive, a flash memory, a read-only memory (ROM), a CD, a DVD, a cache, a random-access memory (RAM) and/or any other storage media in which information is stored for any duration (e.g., for extended time periods, permanently, brief instances, for temporarily buffering, and/or for caching of the information). A computer program may comprise the computer executable instructions. The computer readable medium may be a tangible or non-transitory computer readable medium. The term "computer readable" encompasses "machine readable".

The singular terms "a" and "an" should not be taken to mean "one and only one". Rather, they should be taken to mean "at least one" or "one or more" unless stated otherwise.

The word "comprising" and its derivatives including "comprises" and "comprise" include each of the stated features but does not exclude the inclusion of one or more further features.

The above implementations have been described by way of example only, and the described implementations are to be considered in all respects only as illustrative and not restrictive. It will be appreciated that variations of the described implementations may be made without departing from the scope of the disclosure.

It will also be apparent that there are many variations that have not been described, but that fall within the scope of the appended claims.

List of references: 1 Electric vehicle (EV) 2 Cloud 3 EV charging facility ("Forecourt") 4 EV charging facility status display EV charging point(s) within EV charging facility Data Capture Module 21 Battery charge level CYO 22 EV location 23 Estimated time of arrival 24 EV direction ("heading") Energy Supply and Demand Processing Unit EV Charge Offer Module 41 EV charge offer(s) 20 100 System 101 Isochrone 102 Geographical region Determining charge point status 111 Determining availability of charge point status 112 Checking supply level 113 Decreasing lsochrone (reducing pool of prospective customers for issuance of EV charge offers) 114 Increasing Isochrone (increasing pool of prospective customers for issuance of EV charge offers) 115 Confirming Isochrone 116 Determining prospective customers 117 Issuing EV charge offer(s) 118 Checking offer accepted 119 Reserving EV charging point within EV charging facility and updating forecourt status 120 Checking EV arrival at forecourt 121 Releasing booking 122 Registering EV charging session and updating customer account

Claims

CLAIMS: 1. A system for managing energy supply and demand at an EV charging facility, the system comprising: a data capture module configured to receive data representative of: a) a plurality of EVs corresponding to a plurality of respective prospective customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations; and d) energy supply availability at the EV charging facility; an energy supply and demand processing unit programmed to determine a subgroup of said plurality of EVs and corresponding prospective customers based on said received data; and, an EV charge offer module, the EV charge offer module being configured to issue EV charge offers to said prospective customers subgroup, wherein said EV charge offers each include at least a proposed EV charging time at the EV charging facility.
2. A system according to claim 1, wherein the data capture module is configured to further receive reservation confirmations corresponding to one or more of said EV charge offers; optionally, wherein said reservation confirmations are customer generated.
3. A system according to claim 1 or 2, wherein the data capture module is configured to further receive customer generated reservation requests.
4. A system according to claim 2 and/or 3, wherein the energy supply and demand processing unit is further programmed to reserve one or more EV charging points provided at the EV charging facility based on said reservation confirmations or requests.
5. A system according to any one of claims 1 to 4, wherein the data capture module is configured to further receive data representative of e) EV journey, wherein said EV journey data may comprise data representative of any one or more of: a battery charging state; a power input, such as an instant or average power input; a power output, such as an instant or average power output; a remaining driving range; a direction, such as a direction relative to the EV charging facility; a speed, such as an instant or average speed; and an identifier of either the EVs, such as a Vehicle Identification Number, or of a telematics device attached to the EVs.
6. A system according to any one of claims 1 to 5, wherein the energy supply and demand processing unit is programmed to include any one or more of the EVs and corresponding prospective customers in said subgroup: if the EV locations of said one or more EVs are within a geographical region disposed around the EV charging facility; and/or, if the EV charge levels of said one or more EVs are below an upper charge level threshold and/or above a lower charge level threshold.
7. A system according to claim 6, wherein the energy supply and demand processing unit is further programmed to define said geographical region by one or more of: a radial distance from the EV charging facility; one or more lines defined by one or more respective roads and, an isochrone relative to the EV charging facility; and/or, wherein the energy supply and demand processing unit is further programmed to define said upper and lower charge level thresholds.
8. A system according to claim 6 or 7, wherein the energy supply and demand processing unit is further programmed to adapt said geographical region and/or said upper and lower charge level thresholds to the data received by the data capture module.
9. A system according to claim 6, 7 or 8 when depending from claim 2, wherein the energy supply and demand processing unit is programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said reservation confirmations.
10. A system according to any one of claims 6 to 9 when depending from claim 3, wherein the energy supply and demand processing unit is programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said user generated reservation requests.
11 A system according to any one of claims 6 to 10 when depending from claim 4, wherein the energy supply and demand processing unit is programmed to adapt, or further adapt, said geographical region and/or said upper and lower charge level thresholds to said reservations of the one or more EV charging points provided at the EV charging facility.
12. A system according to any preceding claim, wherein said proposed EV charge time comprises a proposed EV charge time or time interval within which an EV charge operation is to be started and/or completed.
13. A system according to any preceding claim, wherein said EV charge offers comprise one or more allocated EV charge offers that specify one or more EV charge points provided at the EV charging facility.
14. A system according to any preceding claim, wherein the EV charge offers comprise one or more incenfivised EV charge offers that specify at least one incentive for the customer to accept said incentivised EV charge offers.
15. An app for communicating with a system according to any one of the previous claims, the app being configured: to send to the data capture module data representative of an EV corresponding to a prospective customer of the EV charging facility, EV charge level and EV location; and, to receive from the EV charge offer module one or more EV charge offers.
16. An app according to claim 15, wherein the app is further configured: to generate one or more reservation confirmations for sending to the data capture module; optionally, wherein said one or more reservation confirmations are user generated.
17. An app according to claim 15 or 6, wherein the applet is further configured: to generate one or more user generated reservation requests for sending to the data capture module.
18 An app according to claim 15, 16 or 17, wherein the app is further configured: to output to the customer the one or more received EV charge offers and/or reservations of the one or more EV charging points at the EV charging facility based on said one or more received EV charge offers.
19. An EV charging facility comprising a system according to any one of claims 1 to 14.
20. A network comprising two or more EV charging facilities, the network comprising a system according to any one of claims 1 to 14, wherein the data capture module is configured to receive data representative of energy availability at the two or more EV charging facilities and wherein said EV charge offers issued by the EV charge offer module each further include at least a proposed EV charging facility of the two or more EV charging facilities.
21. A method of managing energy supply and demand at an EV charging facility, the method comprising: receiving data representative of: a) a plurality of EVs corresponding to a plurality of respective prospective customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations; and, d) energy supply availability at the EV charging facility; determining a subgroup of said plurality of EVs and corresponding prospective customers based on said received data; and, issuing EV charge offers to said prospective customers subgroup, wherein said charge offers each include at least a proposed EV charge time at the EV charging facility.
22. A method according to claim 21, wherein the method further comprises: receiving reservation confirmations based on said EV charge offers, which can optionally be user generated reservation confirmations based on said EV charge offers, or user generated reservation requests; and, reserving one or more EV charge points provided at the EV charging facility based on said reservation confirmations and/or reservation requests.
23. A method of managing energy supply and demand at a network of two or more EV charging facilities, the method comprising: receiving data representative of: a) a plurality of EVs corresponding to a plurality of respective prospective customers of the EV charging facility; b) corresponding EV charge levels; c) corresponding EV locations; and, d) energy supply availability at each of the two or more EV charging facility; determining a subgroup of said plurality of EVs and corresponding prospective customers based on said received data; and, issuing EV charge offers to said prospective customers subgroup, wherein said EV charge offers each include at least a proposed EV charge time relating to at least one of the two or more EV charging facilities.
24. Computer readable medium comprising instructions for performing a method according to claim 21, 22 or 23.