GB2617808A

GB2617808A - System and method for electric vehicle charging

Info

Publication number: GB2617808A
Application number: GB2117679.7A
Authority: GB
Inventors: Mackenzie Hugh
Original assignee: Trojan Energy Ltd
Current assignee: Trojan Energy Ltd
Priority date: 2020-12-07
Filing date: 2021-12-07
Publication date: 2023-10-25
Also published as: WO2022123234A1; GB202019242D0; GB202117679D0

Abstract

The invention provides a method and system for optimising the utilisation of EV charging spaces 12a-h using a processing means. The method comprises receiving in the processing means: parking event data including information relating to the time and location of a vehicle parking event derived from a tracking device of a user; utilisation data representative of the utilisation of a set of EV charging spaces at a known location in the vicinity of the vehicle parking event at a time or in a period of time derived from an observational monitoring system 20; user data including an address associated with a user; and vehicle classification data relating to a vehicle associated with the user. The processing means determines a user-specific output, such as an incentive, based on the parking event data, the utilisation data, the user data and the vehicle classification data. The method further comprises linking the user-specific output to a user account associated with the user to influence the behaviour of the user to improve the utilisation of the set of EV charging spaces.

Description

I SYSTEM AND METHOD FOR ELECTRIC VEHICLE CHARGING

3 The present invention relates to systems and methods for optimising or otherwise 4 improving the utilisation of Electric Vehicle (EV) charging parking spaces. Aspects of the invention relate to systems and method for generating user specific outputs which are 6 capable of prompting and/or influencing user behaviour to improve the utilisation of EV 7 charging infrastructure.

9 Background to the invention

11 Parking bays or areas adjacent to or containing charging facilities for electric vehicles 12 (EVs) -otherwise known as charging spaces -are increasing in number as the 13 infrastructure for EVs is improved and developed. These charging spaces may become 14 blocked by an internal combustion engine (ICE) vehicle, a non-plug-in hybrid vehicle (non-PHEV) or an EV which is not currently using the charging facilities offered by that space.

16 When a charging space is blocked, it cannot be utilised by an EV driver in need of vehicle 17 charging. This is not only an inconvenience for the EV driver, but also a lost earning 18 opportunity for the charging energy supplier (or suppliers). This is a growing problem and 19 one that is particularly prevalent for on-street charging spaces, especially those located in residential areas.

22 Local governments and authorities can be hesitant to implement parking bays containing 23 charging facilities in which only EV drivers can park for policy reasons, for example 24 because such parking bays may be negatively received by individuals who live or work nearby the proposed parking bay sites. Those who drive ICE vehicles or non-PHEVs may 26 be negatively impacted by their inability to park in a designated EV only space (or 27 otherwise risk being penalised or fined).

29 There is an imperative to provide charging facilities in universal parking bays in which all drivers are permitted to park. However, given the potential for these bays to become 31 blocked by drivers not using the charging facilities, a problem exists in how to ensure 32 efficient use of the charging facilities.

34 Given that the provision of charging facilities and charging spaces requires substantial investment and planning, and that installation of charging facilities is generally disruptive, 1 the number of charging spaces that are able to be installed in any one location will be 2 restricted. It is therefore important to ensure efficient utilisation of charging spaces.

4 US 10,192,440 describes a system for displaying parking spaces comprising a camera system which is designed to provide image indicators of parking spaces within a parking 6 lot and a recognition unit. The recognition unit is designed to store the geographical 7 coordinates of parking spaces present in the visual range of the camera system and to 8 assign each parking space a respective occupation status (i.e. available or occupied) 9 based on the image indicators.

11 Summary of the invention

13 It is amongst the aims and objects of the invention to provide a system for and/or method 14 of improving the utilisation of EV charging spaces.

16 It is amongst the aims and objects of the invention to provide a system for and/or method 17 for improving the utilisation of EV charging spaces by rewarding drivers and/or passengers 18 for avoiding or moving out of EV charging spaces if they drive a non-chargeable vehicle 19 (an ICE vehicle or a non-PHEV) or if they drive an EV which at the time of parking is low priority for charging, to enable the charging spaces to be efficiently utilised by EVs which 21 require charging.

23 In particular, one aim of an aspect of the invention is to provide a system for and/or 24 method of optimising the use of EV charging spaces by offering incentives to vehicle drivers and/or passengers to create effective responses and behavioural changes from 26 those drivers and/or passengers, such as moving out of or avoiding a charging space 27 when they do not drive a chargeable vehicle or when charging is low priority.

29 In particular, one aim of an aspect of the invention is to provide a system for and/or method of optimising the use of EV charging spaces by offering targeted incentives to 31 vehicle drivers and/or passengers -including determining which incentive or incentives to 32 offer to certain individual drivers and/or passengers and when to offer them -based on 33 various inputs, to influence the behaviour of vehicle drivers and/or passengers and 34 persuade them to move out of or avoid a charging space when they do not drive a chargeable vehicle or when charging is not required.

1 Other aims and objects of the invention will become apparent from the following

2 description.

4 According to a first aspect of the invention there is provided a method of optimising the utilisation of EV charging spaces, the method comprising: 6 providing a processing means, the processing means being configured to carry out the 7 steps of: 8 a) receiving parking event data including information relating to the time and 9 location of a vehicle parking event derived from a tracking device of a user; b) receiving utilisation data representative of the utilisation of a set of EV 11 charging spaces at a known location in the vicinity of the vehicle parking 12 event at a time or in a period of time derived from an observational 13 monitoring system; 14 c) receiving user data including an address associated with a user; d) receiving vehicle classification data relating to a vehicle associated with the 16 user; and 17 e) determining a user-specific output based on the parking event data, the 18 utilisation data, the user data and the vehicle classification data; 19 wherein the method comprises linking the user-specific output to a user account associated with the user to influence the behaviour of the user to improve the utilisation of 21 the set of EV charging spaces.

23 The steps a) to e) above may be carried out in any order.

The set of EV charging spaces may comprise a plurality of EV charging spaces (including 26 parking bays and parking areas). Each EV charging space in the set of EV charging 27 spaces may be a parking space, bay or area containing or being located adjacent to a 28 charging point such that an electric vehicle parked in the EV charging space is operable to 29 access and use the charging point. The charging point may comprise a charging station.

The charging point may comprise an access connector similar to that described in the 31 applicant's international patent application number WO 2019/002868.

33 The processing means may comprise, but is not limited to, one or more (or a combination 34 of) computers, processors and/or software programmes.

1 The processing means may be located in one or more components of charging 2 infrastructure relating to the set of EV charging spaces. The processing means may be 3 located in and/or operable to communicate with a control and distribution module which 4 may be similar to that described in the applicant's international patent application number WO 2019/002868 and which may be connected to an electrical network and/or a charging 6 point or charging points associated with the set of EV charging spaces.

8 The processing means may be a cloud based processing means, i.e. may be accessed 9 over the internet to store, access and/or process data. The method may therefore store, access and/or process data the using the internet and/or the cloud (e.g. using remote 11 servers accessed over the internet).

13 The parking event data preferably relates to a past or current parking event of the user.

The processing means may communicate with the tracking device (and/or vice versa) to 16 receive the information relating to the time and location of a vehicle parking event via a 17 wireless communication protocol. The tracking device may comprise a global positioning 18 system (GPS) which may be configured to determine the location of the user at an 19 associated time and transmit this information to the processing means. The tracking device may transmit real-time data relating to the location of the user to the processing 21 means. Alternative forms of tracking and tracking technology may be used. Alternatively, 22 or in addition, the tracking device may comprise a device into which the user is able to 23 manually input his or her location details.

The tracking device may be but is not limited to being: a mobile phone, a smartphone, a 26 tablet, a laptop or a satnav. A plurality of user tracking devices may be interchangeably 27 used for a single user.

29 From the location and time information, the processing means is preferably configured to determine whether the user has participated in a parking event (i.e. whether the vehicle 31 associated with the user has been parked), where that parking event took place (i.e. where 32 the vehicle is parked) and at what time that parking event took place (i.e. when the vehicle 33 was parked).

1 The utilisation data may relate to the status and location of each of the EV charging 2 spaces within the set of EV charging spaces. The status of each of the EV charging 3 spaces may relate to whether they are vacant or occupied (or 'occupation status'). If 4 occupied, the status of each of the EV charging spaces may additionally relate to whether they contain an EV and/or if that EV is charging (i.e. an EV charging status).

7 The utilisation data may be based on historical data derived from the observational 8 monitoring system. The utilisation data may be based on trends in data derived from the 9 observational monitoring system.

11 The utilisation data may be based on real-time data derived from the observational 12 monitoring system. The utilisation data may be based on data derived from the 13 observational monitoring system at time intervals.

The time or period of time may be the current time, or may include the current time. The 16 time or period of time may be a future time or period of time. The time or period of time 17 may be a time or period of time in the immediate future. Utilisation data could be received 18 by the processing means again, representative of the utilisation of a set of EV charging 19 spaces at a known location in the vicinity of the vehicle parking event at a later time or in a later period of time.

22 The processing means may communicate with the observational monitoring system 23 (and/or vice versa) to receive the utilisation data representative of the utilisation of a set of 24 EV charging spaces at a time or in a period of time using a wireless communication protocol.

27 The location of the vehicle parking event may be in or within a radius of the known location 28 of the set of EV charging spaces.

The observational monitoring system may monitor the set of EV charging spaces. The 31 observational monitoring system may additionally monitor ordinary parking spaces.

33 The observational monitoring system may comprise one or more camera units. The 34 observational monitoring system may comprise an image processor which run image 36 processing software. The image processing software may be run using the internet and/or 1 store or access data using the cloud. The one or more camera units and the image 2 processing software may be configured to Identify the position of a parked vehicle and/or a 3 parking space (including a charging space). The one or more camera units and the image 4 processor may be configured to determine the GPS coordinates of a parked vehicle and/or a parking space (including a charging space). The one or more camera units and the 6 image processor may be configured to: produce images of spaces, areas or vehicles 7 within the set of EV parking spaces; store the geographical coordinates of the spaces, 8 areas or vehicles; determine the status of a space, area or vehicle (i.e. if a space or area is 9 available or occupied and/or if a vehicle is parked) based on the images; and relate the geographical coordinates with the status to identify where available and/or occupied 11 spaces or areas are located and/or where a vehicle is parked. The one or more camera 12 units and the image processor may be configured to determine one or more GPS 13 coordinates associated with a parked vehicle. For example, the observational monitoring 14 system may be configured to determine the GPS coordinate of each corner of a parked vehicle. The one or more camera units and the image processor may be configured to 16 transmit the GPS coordinate data and/or status data to the processing means.

18 The one or more cameras may be solar powered. The one or more cameras may be 19 mounted at a position elevated from street level, which may increase (lengthen and/or widen) their field of view. The one or more cameras may be mounted on a streetlight post.

21 The one or more cameras may be operable to generate a video output. The one or more 22 cameras may be operable to generate a plurality of still, image outputs. The outputs of the 23 one or more cameras may be provided continuously, at regular or at irregular time 24 intervals.

26 The image processing may be performed remotely from the camera units, such as by or in 27 the processing means.

29 The observational monitoring system may comprise one or more sensors. The observational monitoring system may comprise one or more vehicle detection sensors.

31 The vehicle detection sensors may be located on or in the ground, on a surface and/or 32 overhead. The one or more vehicle detection sensors may include one or more sensors 33 selected from the non-exhaustive group of: inductive sensors, ultrasonic sensors, 34 magnetic sensors (including magnetometers and inductive sensors), light sensors and 1 proximity sensors. The observational monitoring system may comprise processing 2 software.

4 The set of EV charging spaces may be located in a field of view of the one or more cameras.

7 The observational monitoring system may be operable to determine the classification of a 8 vehicle locating in an EV charging space and/or a parking space (i.e. whether it is an ICE 9 vehicle, a non-PHEV or an EV) and thus whether it is a chargeable vehicle or a non-chargeable vehicle.

12 The observational monitoring system may be operable to determine whether a vehicle is 13 connected to a charging point associated with an EV charging space of the set of EV 14 charging spaces.

16 The processing means may communicate with a plurality of observational monitoring 17 systems. The plurality of observational monitoring systems may be spatially distributed 18 over different streets, roads, car parks, areas and/or localities to monitor a plurality of sets 19 of EV charging spaces. The observational monitoring system, a plurality of observational monitoring systems and/or the processing means may build up a picture spanning an area 21 comprising a plurality of EV charging spaces to determine information relating to a plurality 22 of parking spaces and/or charging spaces, including the availability for use of those 23 parking spaces or charging spaces, monitored by the observational monitoring system(s).

The user data may be associated with the user account associated with the user. The user 26 account may communicate with or be stored in or on the processing means. The user 27 account may communicate with the processing means via a wireless communication 28 protocol The user account may contain information which may be input by a user and which may 31 be stored and/or hosted on the cloud.

33 The information may have been or may be inputted into the user account and/or edited or 34 accessed by the user using a user interface device (which may be the same device as the tracking device). The information may be inputted to the user account and/or edited or accessed by the user via a website and/or an application on the user interface device.

2 Preferably, the user account is accessed using an app on a smartphone.

4 The address associated with the user may be, but is not limited to being, a residential home address, the address of a friend or a relative and/or a workplace address. The user 6 data may comprise more than one address.

8 The user data may include additional information. The user data may include, but is not 9 limited to, one or more of: the name of the user; II -the make and model of vehicle driven by the user; 12 -the age of the user; 13 -the gender of the user; 14 -a charging history of the user (i.e. when, for how long, where and at which rate a user has charger their EV); 16 -a payment history of a user (i.e. payment for EV charging -how much a user tends 17 to spend in a charging session, whether payments have been late, whether the 18 user has debt associated with a payment account); 19 -an incentive history of the user; and/or -a parking location history of the user.

22 The incentive history of the user may be data relating to incentives / rewards historically 23 selected by the user from the user-specific output. The incentive history of the user may be 24 useful as it can be used to determine which incentives / rewards are more appealing and therefore persuasive to the user and which incentives / rewards are therefore more likely 26 to motivate the driver to avoid parking in EV charging spaces now and in the future and/or 27 to move out of an EV charging space.

29 The vehicle classification data may relate to the type of the vehicle associated with the user and may inform the processing means whether the user drives an ICE vehicle, a non- 31 PHEV or an EV. The vehicle classification data may be provided to the processing means 32 via the user account. The vehicle classification data may be provided to the processing 33 means via the observational monitoring system.

1 The processing means may be configured to carry out additional steps before determining 2 the user-specific output.

4 The processing means may be configured to carry out one or more of the steps.

The processing means may be configured to communicate with some or all of the EV 6 charge points associated with the set of EV charging spaces. Communication may be 7 direct or indirect, via one or more components.

9 The processing means may be configured to receive data relating to the charge rate that an EV can support (i.e. whether it can receive charging at 3kW, 7kW and/or 22 kW). This 11 data may be derived from the observational monitoring system. This data may be derived 12 from the user data. Charging at a higher rate, such as 22kW, is faster. The processing 13 means may therefore use this data in the arbitration of power, to optimise utilisation of the 14 charging spaces by managing maximum charge capacity. For example, the processing means might hold data relating to the total possible load draw for the set of EV spaces. By 16 relating this information to expected or known high demand periods for charging (which 17 may be derived from the observational monitoring system) in the spaces as well as the 18 possible charge rates of EV vehicles currently parked in a charging space, the processing 19 means can determine whether one or more of the EVs currently connected for charging should be moved to a higher charging rate (i.e. from 7kW to 22kW) to speed up charging 21 and increase the capacity that will be available for the high demand period. In this way, 22 when the high demand period begins or occurs, the total possible load draw will no longer 23 need to be shared by the vehicles which were moved to 22kW fast charging in advance.

To determine the user-specific output the processing means may relate all or some of the 26 parking event data, the utilisation data, the user data and the vehicle classification data to 27 each other.

29 The user-specific outputs which are awarded or offered to a user may vary for different subsets of users, which may be demographically split groups of users. This may be done 31 to offer incentives which are likely to be or have been determined to be more attractive to 32 users in those groups. Subsets may be arranged in one or more of the following non- 33 exhaustive list of groups: age range, gender, location (i.e. post-code), interests, vehicle 34 classification and/or occupation.

1 To determine the user-specific output, the processing means may process some or all of 2 the data that it receives. This may be done using one or more algorithms.

4 The processing means may process some or all of the data that it received to determine one or more of: 6 -charging history trends of the user or for an area; 7 - incentive history trends of the user; 8 -parking location history trends of the user or for an area; 9 -parking behaviour trends of the user or for an area (for example, where a user (or various users) tends to park when the weather is bad or late at night, if the user 11 tends to block charging spaces or if the user does not tend to block charging 12 spaces).

14 The method may comprise using machine learning which may detect and/or identify trends in the data which may be user specific and/or location or area specific.

17 The user-specific output may relate to an incentive and/or a choice of incentives available 18 the user. The availability of the incentive or choice of incentives may be conditional. For 19 example, where the processing means determines that a parking event takes place in an EV charging space and that the user drives an ICE vehicle, the availability of the incentive 21 may be conditional on the user moving their vehicle out of the EV charging space to 22 motivate the user to move their vehicle. The availability of the incentive or choice of 23 incentives may be un-conditional. For example, where the processing means determines 24 that a parking event takes place somewhere other than in an EV charging space, the un-conditional award of an incentive and/or a choice of incentives may encourage a user to 26 continue to avoid parking in EV charging spaces.

28 Some or all of the data received by the processing means may be stored in one or more 29 databases to identify trends. For example, historic data relating to parking and charging may be stored in a database to identify trends in parking and/or charging demand and to 31 determine peak, high demand times.

33 The trends may be used to determine a user-specific output in the form of a targeted 34 incentive for the user.

1 For example, more desirable and/or higher value incentives may be offered to the user to 2 encourage the user to avoid EV charging spaces at high demand / peak times for EV 3 charging or parking on the street or area.

In another example, more desirable and/or higher value incentives may be offered to the 6 user if the set of EV charging spaces is located in front of or close to the address 7 associated with the user.

9 Subsets of users (for example, demographically split groups of users) may be offered incentives which are likely to be more attractive to them and/or which have been 11 determined as being more attractive based on incentive history. Subsets could be 12 arranged by one or more of the following non-exhaustive list of groups: age, gender, 13 location (i.e. post-code), interests, vehicle classification and/or occupation.

14 The decision of which incentive to offer to a user may be based, in part, on the past incentives that they have selected and/or enjoyed.

17 The user-specific output preferably relates to an incentive (i.e. a reward) which is offered 18 to or made available to the user to motivate the user to park their vehicle somewhere other 19 than in the set of EV charging spaces.

21 To determine the user-specific output the processing means may run one or more 22 algorithms using some or all of the data that it has received.

24 The user-specific output may be the offer of an incentive which may be provided at a certain time. The type of incentive offered may be dependent on the data received by the 26 processing means. The offer of an incentive can advantageously encourage a user to 27 avoid parking in a charging space or to move their vehicle out of a charging space.

29 The user-specific output may be the provision to the user with access to an incentive which may be provided if the user parks somewhere other than the electric vehicle parking 31 space. The provision of access to an incentive can advantageously reward a user for 32 parking somewhere other than an electric vehicle parking space.

1 The user-specific output may be the offer of, or provision of access to, an incentive if the 2 location of the vehicle parking event and the known location of the set of EV charging 3 spaces are within a proximity range of one another.

The user-specific output may be the offer of, or provision of access to, an incentive if the 6 location of the vehicle parking event and the known location of the set of EV charging 7 spaces are within a proximity range of one another and the utilisation data indicates that 8 the set of EV charging spaces has low availability.

The offer of, or provision of access to, an incentive may depend on the availability for use 11 of other charging and/or parking spaces monitored by the observational monitoring system 12 and/or additional observational monitoring systems which may be within a proximity range 13 of the location of the user and/pr the parking event.

The method may comprise providing the user with an incentive, the offer of an incentive, 16 the notification of an incentive or an offer of an incentive, based on the user-specific 17 Output.

19 The method may comprise one or more of the following: -crediting the user account with redeemable points and/or money; 21 -enabling a feature relating to the user account (for example, where the user 22 accesses the user account via a smartphone app, the method may comprise 23 enabling a feature of the smartphone app); 24 sending a notification to the user when the user-specific output is determined; -sending a notification to the user after the user-specific output is determined (for 26 example this may include sending a weekly e-mail or notification to the user to 27 inform them of incentives awarded or offered to them during the past week).

29 The method may comprise sending data, a signal and/or a notification to a user interface device to alert the user of the user-specific output. The user interface device may be the 31 same device as the tracking device and/or as the device on which a user accesses their 32 user account.

34 According to a second aspect of the invention there is provided a system for optimising the utilisation of EV charging spaces, the system comprising: 1 a tracking device associated with a user; 2 an observational monitoring system; and 3 a processing means; 4 wherein the processing means is configured to: receive parking event data including information relating to the time and 6 location of a vehicle parking event derived from the tracking device; 7 receive utilisation data representative of the utilisation of a set of EV 8 charging spaces at a known location in the vicinity of the vehicle parking 9 event at a time or in a period of time derived from the observational monitoring system; 11 receive user data including an address associated with the user; 12 receive vehicle classification data relating to a vehicle associated with the 13 user; and 14 -determine a user-specific output based on the parking event data, the utilisation data, the user data and the vehicle classification data; and 16 wherein the processing means is further configured to link the user-specific output to a 17 user account associated with the user for influencing the behaviour of the user to improve 18 the utilisation of the set of EV charging spaces.

The system may comprise one or more charging points which may be located adjacent to 21 or in the set of EV charging spaces.

23 The processing means may be configured to communicate with and/or send control 24 signals to the one or more charging points.

26 Embodiments of the second aspect of the invention may include one or more features of 27 the first aspect of the invention, or vice versa.

29 Brief Description of Drawincis

31 There will now be described, by way of example only, an embodiment of the invention with 32 reference to the following drawings, of which: 1 Figure 1A is a schematic physical representation of a street containing charging spaces 2 which is a subject of an EV charge space optimisation system according to a first 3 embodiment of the invention; Figure 1B is a schematic physical representation of the components of the EV charge 6 space optimisation system of Figure 1A; and 8 Figure 2 is a block diagram schematic representation of the data streams of an EV charge 9 space optimisation system according to an embodiment of the invention; and 11 Figure 3 is a schematic representation of a method of a method of optimising the use of 12 EV charging spaces in accordance with an embodiment of the invention.

14 Detailed Description

16 A primary objective of the invention is to provide a method and system for optimising the 17 use of EV charging spaces, which provides drivers and/or passengers with incentives and 18 rewards to encourage them to avoid parking their vehicles in the EV charging parking 19 spaces when they do not require the use of EV charging facilities. This may be because they do not drive an EV but instead drive an ICE vehicle or a non-PHEV, or that they do 21 drive an EV but charging is low priority for them (for example because they have sufficient 22 charge levels, they have a charging point at their home or they do not require urgent use 23 of their EV). By rewarding users of the system in this way, the invention aims to change 24 the behaviours and habits of both plug-in chargeable vehicle drivers (i.e. EV drivers) and non-plug-in chargeable vehicle drivers (i.e. ICE vehicle and non-PHEV drivers) to make 26 EV charging spaces available to more drivers who need them, enabling overall better 27 utilisation of the charging spaces.

29 Moreover, embodiments of the invention aim to increase efficiency of the optimisation by determining when to offer incentives to users, which users to offer them to and/or which 31 incentives to offer (for example, how persuasive/valuable the rewards should be). This can 32 be based on various factors including the location of the driver relative to the charging 33 spaces and/or the current or future demand for the EV charging spaces. Embodiments of 34 the invention also aim to offer incentives tailored to specific users. Advantageously, by offering tailored incentives -rather than blanket incentives to all -the system can be more persuasive to individual users and therefore result in better utilisation of EV charging 2 spaces.

4 As it is desirable to avoid the installation of exclusive EV only parking bays, embodiments of the invention can enable charging facilities to be deployed in charging spaces which are 6 available for universal use. By optimising use of the charging spaces negates the need to 7 locate the charging facilities in or next to specially designated EV only parking bays, which 8 makes them more attractive to councils and local authorities. Where better use is made of 9 charging spaces, this enables less charging spaces to be deployed, ultimately reducing the cost and disruption associated with the installation of EV charging facilities.

12 Referring to Figure 1A, there is shown, generally at 10, a street lined with a set of charging 13 spaces 12a-h. On the pavement 13 adjacent to each parking space 12a-h an EV charge 14 point access connector 14a-h is installed (the access connectors 14a-h have been enlarged for clarity). The access connectors 14a-h allow EV drivers to connect their EVs to 16 an electrical network for charging. However, anyone (including ICE vehicle drivers) is able 17 to park in the charging spaces 12a-h, as they are not exclusive EV only parking bays and 18 there is no penalty for doing so. An EV 16 is shown parked in the charging space 12a and 19 is connected to the access connector 14a for charging.

21 Also located on the pavement 13 is a streetlight 18. A camera 20 is mounted on the 22 streetlight which has a field of view which spans all of the charging spaces 12a-h and 23 which captures images of the set of charging spaces 12a-h at regular time intervals. The 24 camera 20 has a local image processing unit. The image processing unit can process the images captured by the camera 20 to determine whether a space 12a-h is available or 26 occupied and, if occupied, whether the occupying vehicle is connected to an access 27 connector 14a-h for charging. GPS coordinates are also assigned to the charging spaces 28 12a-h by the image processing unit.

There several apartment blocks on the street, two of which are shown at 22a and 22b. The 31 street 10 is the subject of an EV charge space optimisation system according to a first 32 embodiment of the invention. The system aims to ensure that the charging spaces 12a-h 33 are efficiently utilised by EVs requiring use of the access connectors 14a-h for charging by 34 offering rewards to users who do not require use of the access connectors 14a-h if they park somewhere else. The system can be programmed to place particular emphasis on 1 influencing the behaviour of the residents of apartments blocks 22a and 22b, who are most 2 likely to want to park in the spaces 12a-12b. This could be done by offering the residents 3 more regular incentives and/or more desirable incentives. The EV charge space 4 optimisation system might be programmed to offer rewards only at busy, high demand times.

7 It will be appreciated that although access connectors are described, the invention can be 8 implemented for alternative charging points including conventional charging stations 9 and/or a combination of charging facility types. It will also be appreciated that although a single street is described as being the subject of the EV charge space optimIsation 11 system, the system can span larger areas and can, for example, be countrywide or 12 nationwide.

14 Figure 1B shows the main components of the EV charge space optimisation system according to the first embodiment of the invention. These include: the streetlight camera 16 20, a cloud-based processing unit 24 and a smartphone 26 of a driver. The driver has 17 downloaded an app on the smartphone 26 and created a user account to register for the 18 system services and to gain access to the app content. When creating his or her user 19 account, the driver is required to provide certain information about him or herself and the vehicle that they drive. The smartphone 26 is also enabled with GPS which shares the 21 location of the driver with the cloud-based processing unit 24. From this information, the 22 cloud-based processing unit can determine if a user has parked their vehicle (or is a 23 passenger in a vehicle that has been parked), at what time the vehicle was parked and 24 where it was parked.

26 The smartphone 26 and the streetlight camera 20 communicate wirelessly with the 27 processing unit 24 to provide it with the information it needs to determine whether or not to 28 offer or provide the driver with an incentive. If an incentive is offered or provided, the 29 processing unit 24 sends a notification to the driver via his or her user account. As described above, this can be accessed via the app on the smartphone 26.

32 Although only one smartphone 26 is shown and one vehicle driver is described, the 33 processing unit 24 communicates with multiple GPS enabled user tracking devices - 34 including but not limited to smartphones, tablets and satellite navigation devices (sat nays) -of a number of users to build up a comprehensive picture of charging space demand and 2 the relative location(s) of vehicle drivers participating in the system.

4 Figure 2 is a block diagram schematic representation of an EV charge space optimisation system 100 which shows, more clearly, the various inputs used in determining how to 6 optimise charge space utilisation by offering vehicle drivers rewards for parking 7 somewhere other than the charging spaces. The cloud-based data processing unit 124 8 receives information from various data streams to determine when and to whom to offer 9 incentives, and what incentives to offer.

11 A first input stream comes from the streetlight camera 120 which is ideally positioned to 12 monitor a cluster of parking spaces. The cluster can contain both ordinary parking spaces 13 and charging spaces.

The streetlight camera 120 captures real-time images of the cluster of spaces and uses 16 image processing software to determine the number of vacant and occupied spaces in the 17 cluster. The software is also able to classify of the type of vehicle in a space (i.e. as an ICE 18 vehicle, a non-PHEV or an EV) and thus determine whether a chargeable vehicle or a 19 non-chargeable vehicle is parked in one of the spaces. It can additionally determine whether a vehicle is connected to the associated charging infrastructure. Using this 21 information, the data processing unit 124 can ultimately determine whether a charging 22 space is being blocked by a vehicle not making use of the charging facilities. This may 23 result in an incentive offer being made to the driver of that vehicle.

A second input stream 128 to the processing unit 124 relates to the EV charging points 26 associated with the cluster of charging spaces. The location of each of the EV charging 27 points (or spaces) is known to the processing unit 124. This could be achieved by 28 manually entering the co-ordinates for each charging point into the processing unit 124.

29 Alternatively, the charging points or spaces could have inbuilt GPS or other location sensors.

32 Optionally, each charging point is operable to communicate with the data processing unit 33 124 to transmit data to the processing unit 124 relating to whether or not it is in use (i.e. 34 whether it is actively connected to and charging an EV). Receiving this data directly from the charging points provides the data processing unit 124 with a certain indication of 1 whether a charging point is in use. In contrast with the determination made from the image 2 processing software which might incorrectly determine, or find it difficult to determine, 3 whether a charging point is or is not in use when a vehicle is parked in a charging space.

A third input stream to the processing unit 124 comes from a location tracking device 126a 6 of each vehicle driver, to provide the unit 124 with the real-time location of users. This 7 information is used by the processing unit 124 to identify whether a parking event has 8 taken place and to determine more information about that parking event (which might 9 include where and when the parking event has taken place). The processing unit 124 can therefore determine whether a vehicle has been parked in an EV space within the cluster.

11 This determination may also rely on data provided by the streetlight camera.

13 The tracking data is provided by a GPS enabled smartphone (although can alternatively be 14 provided by sat nays, tablets and other location service enabled devices or a combination of these devices). To allow a smartphone to wirelessly communicate with the data 16 processing unit to provide it with the required location information, a vehicle driver can 17 access a website or application of the system using their smartphone and enable this 18 service.

Using location services, the tracking device 126a or the data processing unit 124 can 21 further determine whether a vehicle driver is stationary or moving, at which speed they are 22 moving at and in which direction they are moving to identify whether they are currently 23 driving and/or approaching a cluster of charging spaces. This may impact whether or not 24 an incentive is made available to them.

26 Other information that can be provided to the data processing unit 124 (or determined by 27 it) from the location of a vehicle driver include the weather and the time at the vehicle 28 driver's location. This information can be incorporated into the determination of whether to 29 offer or provide a vehicle driver with an incentive and the level of that incentive (for example, higher incentives might be offered to users if they are asked leave charging 31 spaces near their home late at night or in bad weather) and/or can be used to predict the 32 behaviour of users.

34 As described above, to participate in the system each driver must create a user account. A fourth input stream to the processing unit 124 comes from the user account data 126b.

1 The user account is accessed and used via a website or an application, which a user can 2 access using, for example, a computer, tablet or smartphone. Users can engage with the 3 system using a user interface device such as a tablet, computer, and/or smartphone; 4 however, users may also be able to engage with the system via roadside infrastructure such as charging stations. A dashed line is provided between the location tracking device 6 input stream 126a and the user account input stream 126b to represent that both input 7 streams can be facilitated by the smartphone of a vehicle driver.

8 The user account provides the data processing unit 124 with the identify and address of 9 each user. In addition, the user account informs the data processing unit of the type of vehicle the user drives (EV, ICE vehicle or non-PHEV) and therefore whether they can 11 make use of EV charge points. The user account also stores historical data relating to 12 each drivers activity, including (if they drive an EV) their charging history (including when 13 and where they have made use of charging, patterns in charging and durations of 14 charging) and incentive history (including types of incentives chosen / most persuasive, responsiveness to incentives and incentive patterns).

17 If a driver drives an EV, the EV or a device operable to communicate with the EV may 18 transmit data relating to battery the charge levels of the EV to the data processing unit 19 124.

21 The data processing unit 124 can use the information provided from the various input 22 streams to deduce a number of factors which can be used to determine whether an 23 incentive should to be offered to a driver, and what that incentive should be, to optimise 24 the use of charging spaces. These can include, but are not limited to: -The address of a vehicle driver relative to the location of charging points. If a 26 vehicle driver lives nearby or directly beside a cluster of charging spaces they may 27 be offered better incentives, as the likelihood of them parking in a charging space 28 is higher.

29 -The location and/or availability of charging spaces relative to a vehicle drivers location (or relative to the location of their residence or workplace).

31 -The location of other vehicle drivers relative to a vehicle drivers location and/or 32 relative to other charging spaces.

33 -The incentives most likely to result in successful avoidance of or movement from 34 charging spaces for individual vehicle drivers.

-The incentives available to vehicle drivers based on the type of vehicle they drive.

- When a vehicle drivers is most likely to park in a charging space (for example, at night, in the rain, when it is not busy).

- Patterns in the behaviour of a vehicle drivers, or of various vehicle drivers at a certain location or time.

Based on one or more factors determined from the multiple input streams, the data processing means 124 can generate a user-specific output, by determining whether or not to offer an incentive to a vehicle driver and what incentive to offer them. The data processing means 124 produces an output 126c to communicate the offer or availability of a reward to a user. A dashed line is shown between the output 126c, the location tracking device input stream 126a and the user account input stream 126b to show that the output 126c and both input streams 126a and 126c can be facilitated by the smartphone of a vehicle driver. In this case, a vehicle driver will receive an incentive offering via a notification on their smartphone which they will be rewarded if they avoid or move from a charging space or they will receive an incentive via a notification should they park somewhere other than in a charging space.

The incentives which are made available or offered may change depending on the parking situation on a street or in a locality at any one time. For example, if demand for charging spaces is high then drivers in the local area may be eligible for higher rewards than usual if they park somewhere other than the charging spaces. In another example, the system may not offer an incentive if the demand in the area for charging spaces is low or if a vehicle driver does not park in a charging space or does not have a history of parking in and blocking charging spaces.

The rewards offered can include, but are not limited to: money off or credit towards future EV charging, money off or credit towards an EV charging component, money off or credit towards a parking permit for the street, redeemable points, the chance of winning a monetary reward by playing a game such as spin the wheel, product prizes, videos of recognition/celebration, parking availability notifications, having local charging facilities play a song or light up in various colours or patters, and environmental saving notifications (such as % reduction in CO2 emissions of the street or wider area). Drivers may also be ranked against other drivers participating in the system in the local area and/or in the country. If a driver performs well in comparison to other drivers, they could receive a larger reward.

2 Drivers can be given the choice of an award from several options. In alternative 3 embodiments, the drivers may be awarded with points or credits which they can redeem 4 against certain rewards.

6 A vehicle driver may have to qualify for certain incentives. For example, the system may 7 only offer charging space availability information as an incentive to a driver who has 8 established a history (known by the system) of charging an EV (i.e. an EV driver). The 9 reward of charging space availability notifications is particularly appealing to EV drivers because this information will allow EV drivers to receive a notification, in real time, 11 informing them when and where a charging space becomes available. An EV driver may 12 decide to move their EV into the charging space, when notified, to make use of the 13 charging facilities. By offering the reward of parking availability notifications to EV drivers 14 only -and withholding this information from ICE vehicle and non-PHEV drivers -the system gives EV drivers an advantage. The advance notice gives EV drivers a head-start 16 to move into available charging spaces to support utilisation of the charging spaces by EV 17 drivers who need or want to use the charging facilities.

19 Figure 3 is a schematic representation of a method of optimising the use of EV charging spaces, for drivers who EVs and require use of the EV charging facilities according to an 21 embodiment of the invention. The method, generally shown at 200, is carried out by a 22 cloud-based processing unit and includes receiving real-time tracking data from a users 23 GPS enabled smartphone 230. Using this data, the processing unit can determine whether 24 the user is in a vehicle which has parked and if the vehicle has been parked in an EV charging space. The processing unit continuously searches for known charging spaces 26 within a fixed radius of the driver's location 232 and receives availability information for 27 those charging spaces 234 from a camera monitoring system. Each camera monitoring 28 system oversees a cluster of charging spaces and may also monitor non-charging spaces 29 and their availability.

31 The processing unit optionally accounts for other factors 236, including primarily the 32 drivers residential address and the type of vehicle that they drive. This data is associated 33 with the user account/profile with the driver and is shared with or stored in the processing 34 unit. This information can be used to determine whether they can make use of EV charging facilities in the charging spaces. This information can also be used to determine if 1 the driver is likely to have a preference for or tendency to use certain spaces because they 2 are close to the drivers' home. In addition to this information, the processing unit can 3 receive and/or process further data and data trends.

By processing the data, which might include determining the current or projected future 6 demand for charging spaces and/or the proportion of charging spaces in an area currently 7 blocked by ICE vehicles, the processing means will determine whether it needs to 8 implement optimisation of the charging spaces 238. To generate a user-specific output to 9 support optimisation of the charging spaces, the method includes determining the status of the driver 240. Using the tracking data and the camera monitoring system (at least) the 11 processing means will determine whether a driver is stationary (i.e. parked) in a charging 12 space or in an ordinary parking space. If the driver has parked in an ordinary parking 13 space on their own, without receiving a prompt to do so from the system, then they may 14 optionally be notified that they have been provided access to a reward 242. This can help to encourage the driver's good practice of avoiding the EV charging spaces. Alternatively, 16 the system may not offer the driver anything. If the driver has parked in an EV charging 17 space and they are not using the charging facilities -or even if they are using the charging 18 facilities but are low priority for charging -the method includes offering them an incentive 19 to move out of the charging space 244. After moving out of the space, the method may provide them with access to the reward or take steps to implement the reward. If the driver 21 is moving around and is judged to be approaching the charging spaces, then the method 22 might include offering the driver a reward if they do not enter the charging spaces 246.

23 After parking elsewhere, the method may provide the driver with access to the reward or 24 take steps to implement the reward.

26 In this way, the method aims to allow EV drivers to make efficient use of the charging 27 spaces, however limited in quantity. The invention aims to influence the behaviour of 28 drivers so that charging spaces can be better utilised by EV drivers who require access to 29 charging facilities.

31 The invention provides a method and system for optimising the utilisation of EV charging 32 spaces. The method comprises providing a processing means which receives: parking 33 event data including information relating to the time and location of a vehicle parking event 34 derived from a tracking device of a user; utilisation data representative of the utilisation of a set of EV charging spaces at a known location in the vicinity of the vehicle parking event 1 at a time or in a period of time derived from an observational monitoring system; user data 2 including an address associated with a user; and vehicle classification data relating to a 3 vehicle associated with the user. The processing means determines a user-specific output 4 based on the parking event data, the utilisation data, the user data and the vehicle classification data. The method further comprises linking the user-specific output to a user 6 account associated with the user to influence the behaviour of the user to improve the 7 utilisation of the set of EV charging spaces.

9 Various modifications to the above-described embodiment may be made within the scope of the invention, and the invention extends to combinations of features other than those 11 expressly claimed therein.

Claims

1 Claims 3 1. A method of optimising the utilisation of EV charging spaces using a processing 4 means, the method comprising: receiving in the processing means: 6 parking event data including information relating to the time and 7 location of a vehicle parking event derived from a tracking device of a user; 8 utilisation data representative of the utilisation of a set of EV charging 9 spaces at a known location in the vicinity of the vehicle parking event at a time or in a period of time derived from an observational monitoring system; 11 user data including an address associated with the user; and 12 vehicle classification data relating to a vehicle associated with the user; 13 determining a user-specific output based on the parking event data, the utilisation 14 data, the user data and the vehicle classification data; and linking the user-specific output to a user account associated with the user to 16 influence the behaviour of the user to improve the utilisation of the set of EV 17 charging spaces.19

2. The method according to claim 1, wherein the processing means stores, accesses and/or processes data the using the internet and/or the cloud.22

3. The method according to claim 1 or claim 2, wherein the utilisation data comprises a 23 vacant or occupied status and a location of each EV charging space.

4. The method according to any preceding claim, wherein the utilisation data comprises 26 an EV charging status of each EV charging space.28

5. The method according to any preceding claim, wherein the utilisation data comprises 29 one or more of the following: historical data derived from the observational monitoring system; trends in data derived from the observational monitoring system; 31 real-time data derived from the observational monitoring system; and/or data derived 32 from the observational monitoring system at time intervals.1

6. The method according to any preceding claim, comprising using the observational 2 monitoring system to determine the GPS coordinates of a parked vehicle and/or an 3 EV charging space within in the set of EV charging spaces.

7. The method according to any preceding claim, comprising using the observational 6 monitoring system to perform one or more of: producing images of an EV charging 7 space, area or vehicle within the set of EV parking spaces; storing GPS coordinates 8 of an EV charging space, area or vehicle; determining a status of an EV charging 9 space, area or vehicle based on images of the EV charging space, area or vehicle; and/or relating GPS coordinates of an EV charging space, area or vehicle with a 11 status of an EV charging space, area or vehicle to identify where available and/or 12 occupied EV charging spaces or areas are located and/or where a vehicle is parked.14

8. The method according to any preceding claim, comprising determining whether a vehicle located in an EV charging space within the set of EV parking spaces is a 16 chargeable vehicle or a non-chargeable vehicle.18

9. The method according to any preceding claim, comprising determining whether a 19 vehicle is connected to a charging point associated with an EV charging space within the set of EV charging spaces.22

10. The method according to any preceding claim, wherein the address associated with 23 the user is one or more of: a residential home address, the address of a friend or a 24 relative, and/or a workplace address.26

11. The method according to any preceding claim, wherein the user data includes 27 information relating to one or more of: a name of the user; a make and model of a 28 vehicle driven by the user; an age of the user; a gender of the user; a charging 29 history of the user; a payment history of the user; an incentive history of the user; and/or a parking location history of the user.32

12. The method according to claim 11, wherein the incentive history of the user 33 comprises data relating to incentives and/or rewards historically selected by the user 34 from the user-specific output.1

13. The method according to any preceding claim, wherein the vehicle classification data 2 comprises the type of vehicle associated with the user selected from the group 3 comprising: an ICE vehicle, a non-PHEV, a plug-in chargeable vehicle or an EV.

14. The method according to any preceding claim, comprising using the processing 6 means to relate all or some of the parking event data, the utilisation data, the user 7 data and the vehicle classification data to each other to determine the user-specific 8 output.

15. The method according to any preceding claim, wherein the method comprises using 11 the processing means to process some or all of the data that it receives to determine 12 one or more of: charging history trends of the user or for an area; incentive history 13 trends of the user; parking location history trends of the user or for an area; and/or 14 parking behaviour trends of the user or for an area.16

16. The method according to any preceding claim, wherein the user-specific output 17 relates to an incentive and/or a choice of incentives available the user.19

17. The method according to claim 16, wherein the processing means determines which incentive and/or choice of incentives to offer to the user based, at least in part, on 21 the past incentives that the user has selected.23

18. The method according to claim 16 or claim 17, wherein the user-specific output is a 24 conditional incentive and/or choice of incentives which is only provided on the condition that the user parks somewhere other than in an EV charging space within 26 the set of EV charging spaces.28

19. The method according to claim 18, wherein the conditional incentive and/or choice of 29 incentives depends on the utilisation data.31

20. The method according to any of claims 16 to 19, wherein the method comprises 32 providing the user with an incentive, the offer of an incentive, the notification of an 33 incentive or an offer of an incentive, based on the user-specific output.

21. The method according to any preceding claim, comprising one or more of the 2 following: crediting the user account with redeemable points and/or money; enabling 3 a feature relating to the user account; sending a notification to the user when the 4 user-specific output is determined; and/or sending a notification to the user after the user-specific output is determined.7

22. The method according to any preceding claim, comprising sending data, a signal 8 and/or a notification to a user interface device to alert the user of the user-specific 9 output.11

23. A system for optimising the utilisation of EV charging spaces, the system comprising: 12 a tracking device associated with a user; 13 an observational monitoring system; and 14 a processing means; wherein the processing means is configured to: 16 receive parking event data including information relating to the time and 17 location of a vehicle parking event derived from the tracking device; 18 receive utilisation data representative of the utilisation of a set of EV 19 charging spaces at a known location in the vicinity of the vehicle parking event at a time or in a period of time derived from the observational monitoring system; 21 receive user data including an address associated with the user; 22 receive vehicle classification data relating to a vehicle associated with the user; 23 and 24 determine a user-specific output based on the parking event data, the utilisation data, the user data and the vehicle classification data; 26 wherein the processing means is further configured to link the user-specific output 27 to a user account associated with the user for influencing the behaviour of the user 28 to improve the utilisation of the set of EV charging spaces.

24. The system according to claim 23, wherein the observational monitoring system 31 comprises one or more camera units and an image processor which runs image 32 processing software.