Systems and methods for optimizing vehicle charging via location marking

Abstract

This disclosure provides a "system and method for optimizing vehicle charging via location tagging". A location tagging and management system including a transceiver and a processor is disclosed. The transceiver can receive historical trip information and historical charging information associated with a vehicle. The processor can determine a primary location associated with the vehicle from a plurality of locations based on the historical trip information and the historical charging information. The plurality of locations may have been visited by the vehicle historically. When the vehicle is located at the primary location, the processor can also determine the real-time utility power demand in a geographic area including the primary location. The processor can further compare the real-time utility power demand with a predefined demand threshold, and perform a predefined action when the real-time utility power demand is greater than the predefined demand threshold.

Description

Technical Field

[0001] This disclosure relates to systems and methods for optimizing vehicle charging by identifying and marking the vehicle’s primary location, primary charging location and primary parking location. Background Technology

[0002] Electric vehicles (EVs) require regular charging at EV charging stations to ensure optimal vehicle operation. With increasing EV adoption, the number of EVs has surged, leading to a dramatic increase in demand for charging solutions / charging stations. As the number of EVs steadily increases, the growth rate of charging stations needs to match the EV charging demand, ensuring users do not face inconvenience in identifying available charging stations for their vehicles. Therefore, it is crucial for charging infrastructure companies to install the optimal number of chargers in locations where high vehicle charging demand is anticipated. Summary of the Invention

[0003] This disclosure describes a location marking system and method for identifying one or more primary locations associated with a vehicle and optimizing the vehicle charging experience for vehicle users based on the identified primary locations. The primary locations associated with the vehicle can be primary parking locations, primary charging locations, and overall primary locations. A primary parking location can be a location where the vehicle has historically been parked for the longest duration or the highest number of times it has been parked. Similarly, a primary charging location can be a location where the vehicle has historically been charged for the longest duration or the highest number of times it has been charged. The overall primary location can be a location where the vehicle has historically been parked and / or charged for the longest duration and / or the highest number of times it has been charged. For a vehicle, the primary parking locations, the primary charging locations, and the overall primary locations can be the same or different.

[0004] The system can share information associated with identified key locations for multiple vehicles with a charger management company. The charger management company can use this information to estimate vehicle charging demand in one or more geographic areas including the identified key locations and plan accordingly (e.g., in areas with many key locations) the installation of newer chargers. In some respects, the charger management company can be a charging point operator (CPO), a government office focused on site planning for public charging, or any other stakeholder. The system can also use information associated with the identified key locations for vehicles to recommend optimal vehicle charging strategies to vehicle users to enhance their charging experience.

[0005] In some aspects, to identify the primary location for a vehicle, the system can first obtain historical trip information and historical charging information associated with the vehicle. Then, the system can identify the primary parking location for the vehicle based on the historical trip information. Similarly, the system can identify the primary charging location for the vehicle based on the historical charging information. The primary parking location and the primary charging location may be the same or different.

[0006] The system can additionally identify a primary parking confidence level associated with each of the plurality of locations where the vehicle may have historically been visited / parked, and a primary plug-in confidence level associated with each of the plurality of locations where the vehicle may have historically been charged. The system can then calculate a primary confidence level associated with each of the plurality of locations based on the primary parking confidence level or the primary plug-in confidence level. The system can also identify the primary location for the vehicle as the location with the highest primary confidence level.

[0007] In response to determining the primary location for the vehicle, in one exemplary aspect, whenever the vehicle is located at the primary location, the system can monitor real-time utility power demand in a geographic area including the primary location. When the vehicle is located at the primary location and the real-time utility power demand (and therefore energy pricing) is greater than a predefined demand threshold, the system can perform a predefined action. Examples of predefined actions include, but are not limited to, transmitting a command signal to the vehicle to autonomously move the vehicle to a second location different from the primary location (where energy demand / pricing may be low), outputting a first notification including a request to move the vehicle to the second location, outputting a second notification including one or more incentives to be provided to the vehicle user when the vehicle user moves the vehicle to the second location, outputting a third notification including a request to not charge the vehicle at the primary location at the current time (e.g., when energy pricing is high), outputting a command signal to the vehicle plugged in at the primary location to automatically stop charging during a window of high energy demand and resume charging outside of a window of high energy demand, etc. In another aspect, the system can send a notification to a server associated with the charger management company, requesting the company to install one or more new or additional chargers at key locations (e.g., to meet high vehicle charging demand if that high demand is consistent over a relatively long period of time).

[0008] The system can further label the identified primary locations as home, work, etc., based on historical trip information. The system can also label chargers used for vehicle charging as AC chargers, DC chargers, private chargers, public chargers, etc., based on historical charging information.

[0009] This disclosure discloses a location marking system and method that can facilitate charger management companies in identifying locations where newer chargers can be installed. The system can also further facilitate vehicle users charging their vehicles optimally and at lower prices at locations that may differ from the vehicle's primary location (e.g., when energy pricing may be high at the primary location).

[0010] These and other advantages of this disclosure are provided in detail herein. Attached Figure Description

[0011] Specific embodiments are illustrated with reference to the accompanying drawings. The same reference numerals may be used to indicate similar or identical items. Various embodiments may utilize elements and / or components other than those shown in the drawings, and some elements and / or components may not be present in various embodiments. Elements and / or components in the drawings are not necessarily drawn to scale. Throughout this disclosure, singular and plural terms may be used interchangeably, depending on the context.

[0012] Figure 1 An exemplary environment in which the techniques and structures for providing the systems and methods disclosed herein can be implemented is described.

[0013] Figure 2 An example process for identifying and marking the main location of a vehicle according to this disclosure is described.

[0014] Figure 3 Example graphs illustrating multiple parking events of a vehicle over time, according to this disclosure, are depicted.

[0015] Figure 4A and Figure 4B An example process for marking the home and work locations of a vehicle and the type of charger used by the vehicle for charging, according to this disclosure, is described.

[0016] Figure 5 A flowchart is depicted for an example method for optimizing vehicle charging based on the vehicle's primary location, according to this disclosure. Detailed Implementation

[0017] The present disclosure will be described more fully below with reference to the accompanying drawings, which illustrate exemplary embodiments of the present disclosure and are not intended to be limiting.

[0018] Figure 1 An exemplary environment 100 is depicted in which techniques and structures for providing the systems and methods disclosed herein can be implemented. (This will be combined with...) Figure 2 , Figure 3 , Figure 4A and Figure 4B To describe Figure 1.

[0019] Environment 100 may include multiple vehicles 102a, 102b, 102c, 102n (collectively referred to as vehicles 102). Each vehicle 102 may take the form of any passenger or commercial vehicle, such as a car, work vehicle, crossover, truck, van, minivan, taxi, bus, etc. Vehicle 102 may be a manually driven vehicle and / or may be configured to operate in a partially or fully autonomous mode. In an exemplary aspect, each vehicle 102 may be an electric vehicle (EV).

[0020] Environment 100 may also include a location tagging and management system 104 (or system 104) and one or more servers 106 (or server 106). Server 106 may store historical trip information and historical charging information associated with each vehicle 102. In some aspects, the historical trip information associated with each vehicle 102 may include location information of multiple locations 108a, 108b, 108c, 108n (collectively, multiple locations 108) that the vehicle 102 may have visited in the past and / or where the vehicle 102 may have been parked in the past, a count of the number of times the vehicle 102 was parked at each location 108, the duration of the vehicle 102 being parked at each location 108, etc. Server 106 may receive such information directly from each vehicle 102 and store the received information as "trip information". In an exemplary aspect, the location information of the multiple locations 108 is identified based on historical Global Positioning System (GPS) information associated with the vehicle 102 that is periodically received by server 106 from the vehicle 102.

[0021] The historical charging information associated with each vehicle 102 may include charging location information from multiple locations 108, indicating one or more charging locations where the vehicle 102 may have been charged historically, a count of the number of times the vehicle 102 was charged at each charging location, and the charging duration of the vehicle 102 at each charging location. As can be understood, chargers 110a, 110b, and 110c (collectively referred to as charger 110) may or may not be present at each location 108, and therefore, not all vehicle parking locations 108 can be the same as vehicle charging locations. For example, as... Figure 1 As shown, locations 108a, 108b, and 108c can have chargers 110a, 110b, and 110c, and therefore locations 108a, 108b, and 108c can be both parking locations and charging locations for the vehicle (if the vehicle 102 is charging at these locations). On the other hand, since location 108n does not have a charger (or the vehicle 102 may not have been charging at location 108n historically), location 108n can be a parking location for the vehicle, but may not be a charging location for the vehicle.

[0022] In an additional or alternative capacity, server 106 may be associated with a utility power grid and may monitor and store information relating to real-time utility power demand across multiple geographic regions. Alternatively, server 106 may be associated with a charger management company that may install chargers (e.g., charger 110) at different locations across multiple geographic regions. In some respects, the charger management company may be a charging point operator (CPO), a government office focused on public charging site planning, or any other stakeholder.

[0023] System 104 can be communicatively coupled to vehicle 102, charger 110, server 106, etc., via one or more networks. As described herein, the network can be and / or include the Internet, a private network, a public network, or other configurations operating using any one or more known communication protocols such as Transmission Control Protocol / Internet Protocol (TCP / IP), Bluetooth, etc. ® Bluetooth Low Energy (BLE), Wi-Fi based on the IEEE standard 802.11, Ultra Wideband (UWB), and cellular technologies such as Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), High-Speed ​​Packet Access (HSPDA), Long Term Evolution (LTE), Global System for Mobile Communications (GSM), and 5G, to name just a few.

[0024] In some respects, system 104 can be configured to identify one or more “primary” locations associated with each vehicle 102 based on the vehicle’s relevant historical travel and / or charging information, and to facilitate the optimization of the vehicle charging experience for vehicle owners by utility grid companies and / or charger management companies. For example, system 104 can identify primary charging locations, primary parking locations, and overall primary locations associated with each vehicle 102, and use this primary location information to recommend optimal locations where charger management companies can install new chargers and / or optimal locations where vehicle owners can charge their vehicles if real-time utility electricity demand (and therefore energy pricing) is high at the corresponding primary locations of the vehicle owners.

[0025] In an exemplary aspect, the primary parking location for vehicle 102 may be a location where vehicle 102 has historically been parked for the longest duration or the highest number of times. Similarly, the primary charging location for vehicle 102 may be a location where vehicle 102 has historically been charged for the longest duration or the highest number of times. The overall primary location associated with vehicle 102 may be a location where vehicle 102 may have historically been parked and / or charged for the longest duration or the highest number of times. In some aspects, the primary charging location, primary parking location, and overall primary location associated with vehicle 102 may be the same. In other aspects, the primary charging location, primary parking location, and overall primary location associated with vehicle 102 may be different. For example, vehicle 102 may have a primary parking location as location 108a (which may also be the overall primary location of the vehicle) and a primary charging location as location 108c. As another example, vehicle 102 may have a primary parking location, primary charging location, and overall primary location that are the same as location 108a.

[0026] System 104 may be hosted on a server or distributed computing system and may include multiple components, including but not limited to transceiver 112, processor 114, and memory 116. Transceiver 112 may receive / transmit data / information / signals to / from external systems and devices via the network as described above. For example, transceiver 112 may receive historical trip information and historical charging information associated with each vehicle 102 from server 106. Transceiver 112 may also receive information associated with real-time utility electricity demand in one or more geographic areas from server 106. Transceiver 112 may additionally transmit command signals, information, data, etc., to vehicles 102, server 106, etc., via the network.

[0027] Processor 114 may be configured to communicate with one or more memory devices (e.g., memory 116 and / or memory 117) configured to communicate with a corresponding computing system. Figure 1 The processor 114 may communicate with one or more external databases (not shown). The processor 114 may utilize the memory 116 to store programs in code and / or store data to perform aspects of the present disclosure. The memory 116 may be a non-transitory computer-readable storage medium or memory that stores program code that enables the processor 114 to perform operations according to the present disclosure. The memory 116 may include any or a combination of volatile memory elements (e.g., dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), etc.) and may include any one or more non-volatile memory elements (e.g., erasable programmable read-only memory (EPROM), flash memory, electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), etc.).

[0028] In some aspects, memory 116 may include multiple databases and modules, including but not limited to a charging information database 118, a trip information database 120, and a location marking module 122. Charging information database 118 may store historical charging information for vehicle 102 that system 104 may receive from server 106. Similarly, trip information database 120 may store historical trip information for vehicle 102. Location marking module 122 may be stored in memory 116 as computer-executable instructions that can be executed by processor 114 to perform one or more operations as described in this disclosure.

[0029] An example process implemented by system 104 / processor 114 to identify one or more key locations associated with each vehicle 102 and facilitate the optimization of the vehicle charging experience for vehicle owners by utility grid companies and / or charger management companies is described in Figure 2 It is depicted in the text and described below.

[0030] In the first step 202, processor 114 may obtain historical trip information and historical charging information associated with each vehicle 102 from server 106 or directly from vehicle 102 via transceiver 112. In some aspects, processor 114 may obtain historical trip information and historical charging information for a predefined historical duration, such as 3 months, 6 months, 12 months, etc. In one exemplary aspect, the predefined historical duration may be at least 8 weeks. In another aspect, historical trip information and historical charging information may include at least 8 weeks of data, wherein at least one location has been accessed regularly (meaning accessed on average once a week) for up to 6 weeks. Additionally, for newer vehicles that may not have 8 weeks of data, historical trip information and historical charging information may include data wherein at least one location has been accessed regularly (meaning accessed on average once a week) for up to 4 weeks.

[0031] The examples of historical trip information and historical charging information provided above should not be construed as limiting. Historical trip information and historical charging information may be in any other form and / or may cover different historical durations without departing from the scope of this disclosure.

[0032] In response to obtaining the above information, processor 114 may clean up the obtained information at the first step 202 (e.g., remove anomalies, outliers, etc.). Furthermore, in response to obtaining (and cleaning up) the above information, at the second step 204, processor 114 may determine the regularity of parking and charging for each vehicle 102 based on historical travel information and historical charging information. Specifically, at this step, processor 114 may determine, based on the obtained historical travel and charging information, those locations 108 where vehicle 102 may have been parked and / or charged and are potential “competitors” for the primary parking location, primary charging location, and / or overall primary location of vehicle 102. As an example, at this step, processor 114 may include those locations that are potential competitors for the primary location of vehicle 102, wherein vehicle 102 is accessed regularly on average once a week for a span of at least 6 weeks (or 4 weeks for newer vehicles), and inactivity at those locations since the last parking time of vehicle 102 should not exceed 4 weeks.

[0033] In this way, at the second step 204, the processor 114 can determine one or more potential competitors for the primary location (or “first location”) of the vehicle 102 from multiple locations 108 based on historical trip and / or charging information. The parking frequency associated with the vehicle 102 at these first locations or competitor locations may exceed a predefined threshold, from which the processor 114 will identify the primary location, as described later in the following description. As mentioned above, the predefined threshold may be once a week. In other words, the vehicle 102 should be parked and / or charged at a location at least once a week on average (up to 4 or 6 weeks) for that location to be considered one of the first location or competitor locations.

[0034] At the third step 206, processor 114 may prioritize recent vehicle activity, for example, to consider changes in the vehicle's parking and / or charging location due to the vehicle owner moving from one location to another, and / or to consider vehicle activity during holidays. Processor 114 may perform this step by giving recent vehicle activity a relatively higher priority compared to historical vehicle activity and by setting a threshold for locations to be considered for primary location labeling. In an exemplary aspect, at this step, processor 114 may set a reference timeline that is a common timeline during which vehicle 102 travels to all important locations (e.g., the first location mentioned above). In response to setting the reference timeline, processor 114 may ignore or disregard vehicle activity prior to the reference timeline. In other words, processor 114 may not consider locations visited by vehicle 102 before the reference timeline as competitors for primary locations of vehicle 102. Figure 3 The graph 300 depicts an example of the reference timeline 302.

[0035] Graph 300 depicts the distribution of parking events associated with vehicle 102 (on the Y-axis) relative to time (on the X-axis). In this case, as depicted in graph 300, processor 114 can obtain historical travel information of vehicle 102 over the past 12 months, where vehicle 102 may have visited and parked at locations 108a, 108b, 108c, and 108n. Processor 114 can set a reference timeline 302 (between a duration of 6 to 12 months, as shown in graph 300) after which vehicle 102 made trips to locations 108a, 108b, 108c, and 108n. Furthermore, in Figure 3 In the exemplary aspects depicted, vehicle 102 may have been parked at locations 108a, 108b, and 108c more than once a week, and may have been parked at location 108n less than once a week. Therefore, in this case, processor 114 may not consider location 108n as either a first location or a competing location (i.e., a location contending for the primary location label).

[0036] In response to setting the reference timeline 302 as described above, at the fourth step 208, the processor 114 can assign weights to vehicle activities or locations based on the activity timeline. The processor 114 can assign weights such that the most recent vehicle activity (i.e., parking and / or charging at the first location) is given a higher weight than relatively older vehicle activities. The process of assigning weights to locations has been described above. The following description should not be construed as limiting.

[0037] In some aspects, processor 114 can first cluster vehicle trips (including parking and / or charging events) into trip clusters based on the density of trips relative to each other and how close they are. The centroid of the cluster can be used as the address of a first or competitor location 108a, 108b, 108c, etc. For example, processor 114 can cluster parking activities (which may be the number of parking instances in the location and the total parking duration in that location) and charging or plugging activities (which may be the number of plugging instances in the location and the total plugging duration in that location) at each competitor location based on a timeline. Subsequently, processor 114 can normalize the clusters by multiplying them by time-bucket-based weights to obtain a single weighted normalized metric for each location. Example weights are depicted in the table below.

[0038]

[0039] Then, the processor 114 can use the normalized “weighted” data for each location 108a, 108b, 108c to identify the primary charging location, primary parking location, and overall primary location for the vehicle 102, as described below.

[0040] In response to normalizing the data for locations 108a, 108b, and 108c, processor 114 can (e.g., based on weighted or normalized historical trip information) determine a first total duration (“weighted” or “normalized” duration) of vehicle 102 parked at each of these locations and a first count (“weighted” or “normalized” count) of vehicle 102 parked at each of these locations. Thereafter, processor 114 can execute instructions stored in location tagging module 122 to determine / calculate the principal parking confidence (PPC) level associated with each of locations 108a, 108b, and 108c based on the first total duration and the first count. Example mathematical expressions for the PPC for each location are shown below and should not be interpreted as limiting.

[0041] PPC = 0.6 (PPD) + 0.4 (PPI); where if the parking duration is the highest among positions 108a, 108b, and 108c, then the primary parking duration (PPD) = 1, otherwise it is 0, and if the parking instance is the highest, then the primary parking instance (PPI) = 1, otherwise it is 0.

[0042] In a similar manner, processor 114 can (e.g., based on weighted or normalized historical charging information) determine a second total duration (“weighted” or “normalized” duration) of charging of vehicle 102 at each of locations 108a, 108b, and 108c, and a second count of charging frequency (“weighted” or “normalized” count) of vehicle 102 at each of these locations. In some aspects, processor 114 can only determine the second total duration and the second count if it has sufficient historical travel and / or charging information (e.g., at least 8 weeks or more). This is because for newer vehicles, parking information may still be available, and therefore processor 114 can determine the aforementioned first total duration and first count relatively accurately; however, charging information may not be readily available, and therefore processor 114 may not be able to determine the second total duration and the second count accurately.

[0043] In response to determining the second total duration and the second count (e.g., if sufficient historical trip and / or charging information is available), processor 114 may execute instructions stored in location tagging module 122 to determine / calculate the primary plugging confidence level (PPGC) associated with each of locations 108a, 108b, and 108c based on the second total duration and the second count. Example mathematical expressions for the PPGC for each location are shown below and should not be interpreted as limiting.

[0044] PPGC = 0.6 (PPGD) + 0.4 (PPGI); where if the location has the highest plug-in / charge duration among locations 108a, 108b, and 108c, then the primary plug-in duration (PPGD) = 1, otherwise it is 0, and if the location has the highest plug-in / charge instance, then the primary plug-in instance (PPGI) = 1, otherwise it is 0.

[0045] At step 210, processor 114 may determine the primary parking location and / or primary charging or plugging location for vehicle 102 based on the PPC and / or PPGC for each of locations 108a, 108b, and 108c (and therefore based on historical trip information and / or historical charging information for vehicle 102, respectively). In some aspects, the primary parking location may be the location from locations 108a, 108b, and 108c that may have the highest PPC. Similarly, the primary charging or plugging location may be the location from locations 108a, 108b, and 108c that may have the highest PPGC. As mentioned above, the primary parking location may be the same as or different from the primary charging or plugging location.

[0046] At step 212, processor 114 may also determine the overall principal position (from positions 108a, 108b, 108c) for vehicle 102 based on the PPC and PPGC associated with each position 108a, 108b, 108c. Specifically, at this step, processor 114 may first calculate the principal confidence (PC) level associated with each of positions 108a, 108b, 108c based on the PPC and / or PPGC for each position. Example mathematical expressions for the PC for each position are shown below and should not be interpreted as limiting.

[0047] PC = 0.6 (PPGC) + 0.4 (PPC).

[0048] In response to calculating the PC for each of positions 108a, 108b, and 108c, processor 114 can determine the overall principal position for vehicle 102 based on the PC. In an exemplary aspect, processor 114 can determine this position as the overall principal position for vehicle 102, which may have the highest PC among the positions 108a, 108b, and 108c.

[0049] It is understandable that for newer vehicles (or for ICE vehicles), there may not be enough historical charging information available. For such vehicles, the overall primary location can be identified using only parking activity (and therefore only historical trip information), and charging activity can be disregarded (and therefore the PPGC associated with each location 108a, 108b, 108c can be zero). In this case, PC = 0.4 (PPC). Furthermore, in this case, in order to efficiently determine the primary location by differentiating locations in the above scenario (where information availability is low), processor 114 can set / define a minimum difference in parking activity between the primary location and the second primary location. An example procedure for determining the primary location for vehicle 102 when information availability is low is described below.

[0050] In response to determining the PC for each position 108a, 108b, 108c (here, PC = 0.4 (PPC), since PPGC is zero), processor 114 can determine a first potential candidate position from positions 108a, 108b, 108c such that the PC associated with the first potential candidate position is the highest among the PCs associated with positions 108a, 108b, 108c. Processor 114 can also determine a second potential candidate position from positions 108a, 108b, 108c such that the PC associated with the second potential candidate position is the second highest among the PCs associated with positions 108a, 108b, 108c.

[0051] Then, the processor 114 can calculate a first difference between the number of times the vehicle 102 is parked at the first potential candidate location (or parking frequency) and the number of times the vehicle 102 is parked at the second potential candidate location, based on historical trip information. The processor 114 can also calculate a second difference between the total duration of the vehicle 102 parked at the first potential candidate location and the total duration of the vehicle 102 parked at the second potential candidate location, based on historical trip information.

[0052] When a first difference is greater than a first predefined threshold (which could be, for example, 30% of the count of times vehicle 102 is parked at a first potential candidate location) and a second difference is greater than a second predefined threshold (which could be, for example, 50% of the total duration vehicle 102 is parked at a first potential candidate location), processor 114 can select the first potential candidate location as the primary location for vehicle 102. It is understood that processor 114 can implement the above process to ensure accurate determination of the primary location, especially when information availability is low and therefore the probability of misidentification of the primary location is high.

[0053] In response to determining the primary location for vehicle 102 as described above, processor 114 may transmit information associated with the identified primary location and corresponding confidence level to server 106 for storage purposes and / or for further processing at server 106. Whenever vehicle 102 is in a primary location, processor 114 may additionally (based on information obtained from server 106) determine the real-time utility power demand in the geographic area including the primary location. Processor 114 may then compare the real-time utility power demand with a predefined demand threshold and execute a predefined action when the real-time utility power demand is greater than the predefined demand threshold. In other words, processor 114 may execute a predefined action whenever vehicle 102 is in a primary location (e.g., a general primary location or a primary location for parking or charging) and the real-time utility power demand is high.

[0054] Processor 114 can perform predefined actions to optimize the vehicle charging experience. Examples of predefined actions include, but are not limited to, transmitting a command signal to vehicle 102 to cause vehicle 102 to autonomously move to a second location that may be different from the primary location (so that vehicle 102 may charge at a location that may have lower real-time utility power demand and therefore lower energy pricing); outputting a first notification to vehicle 102 and / or a user device associated with the vehicle user, including a request for the vehicle user to move vehicle 102 to the second location; outputting a second notification when the vehicle user moves vehicle 102 to the second location, including one or more incentives (e.g., discounts, free meals, etc.) to be offered to the vehicle user; outputting a third notification including a request for the vehicle user to not charge vehicle 102 at the primary location at the current time (e.g., during peak hours); outputting a command signal to vehicle 102 plugged in at the primary location to automatically stop charging during a window of high energy demand and resume charging outside of a window of high energy demand; and so on.

[0055] In another aspect, predefined actions may include outputting notifications to server 106 associated with the charger management company, including requests to install one or more new chargers at a primary location. In this scenario, the charger management company may monitor such requests for a specific location for a predefined period (e.g., 2-3 months), and thereafter, if server 106 consistently receives such requests for the primary location (indicating a consistently high demand for vehicle charging in and / or the geographic area including the primary location), install a new charger at the primary location (or the geographic area including the primary location).

[0056] Processor 114 may perform one or more additional operations to further enhance the efficiency and accuracy of determining the primary location associated with vehicle 102. Examples of such additional operations are depicted as follows: Figure 2 Steps 214 and 216 are described below. Figure 4A and Figure 4B Example procedure 400.

[0057] As mentioned above, the primary location for parking and charging and the overall primary location for vehicle 102 can be different, because vehicle 102 may be located more frequently in the office but spend more time at home (and can use a public charging port for vehicle charging). In this scenario, the most frequently used public charging location may become the primary location for charging, and the office or home may become the primary location for parking. Furthermore, the overall primary location can depend on the proportion of activity at these two locations (home or office).

[0058] At step 214, processor 114 can tag the vehicle's home location, work / office location, etc., to further enhance the system's primary location identification process. Specifically, at this step, processor 114 can first obtain user input associated with the home location of vehicle 102. As can be understood, when purchasing a vehicle, the user typically provides a purchase address, which can be the user's home address. Processor 114 can obtain this user input (e.g., from server 106) to estimate the vehicle's home address. Then, processor 114 can associate the identified primary location with the home location / address based on the user input. If the identified primary location matches the home location / address, processor 114 can determine that the primary location has been identified with high accuracy. In this case, processor 114 can tag the identified primary location as the vehicle's home location.

[0059] In some respects, if the user does not provide a home location / address, the processor 114 can use the user's or vehicle's parking behavior at a primary location to determine whether it can be classified as a home location. It is understood that most home parking occurs at night, therefore the processor 114 can examine the user's historical parking behavior at the primary location, and if the processor 114 identifies that most parking at the primary location occurs at night, the processor 114 can classify that primary location as a home location for vehicle 102.

[0060] In another aspect, for vehicles without a primary location, processor 114 can utilize a geospatial dataset that details whether the road area is a "commercial" or "residential" area to help determine the possible home location of the vehicle.

[0061] An example process implemented by processor 114 to mark primary locations as home, work, etc. Figure 4A and Figure 4B It is depicted in the text and described below.

[0062] Processor 114 can obtain historical trip and charging information associated with vehicle 102 (as shown in box 402) and determine a primary parking location for vehicle 102 based on the obtained information (as shown in box 404). Processor 114 can then mark the identified location as a primary parking location, as shown in box 406. Processor 114 can then correlate the identified primary parking location with user input, including a home address (if available), or determine the vehicle's parking behavior during nighttime hours, as shown in box 408. When a home address matches a primary parking location, and / or when vehicle 102 is regularly parked at a primary parking location during nighttime hours, processor 114 can mark the identified primary parking location as a home location, as shown in box 410. If vehicle 102 is a fleet vehicle, processor 114 can alternatively mark the identified primary parking location as a primary fleet parking location, as shown in box 412.

[0063] If the processor 114 cannot mark or identify the vehicle's primary parking location, it can check the most common times the vehicle 102 is parked at each location (as shown in box 414), and then mark the location as a home location if the location is in a residential area and the vehicle 102 is parked there during weekday evening hours (as shown in box 416). Furthermore, if the location is in a commercial area and the vehicle 102 is parked there during weekday daytime hours, the processor 114 can mark the location as a "possible" work location (as shown in box 418).

[0064] Processor 114 can also calculate the number of weekly visits to locations marked as potential work locations and the number of weekly hours spent by vehicle 102 at potential work locations to examine key work details, as shown in box 420. If the location is a high-ranking potential work location (i.e., with a high confidence level), processor 114 can examine the location / parking tag (as shown in box 422), and if the location is the vehicle's home location / address, mark the location as "Working from Home" (as shown in box 424). If the location is not the vehicle's home location / address, processor 114 can instead mark the location as a "Primary Work" location, as shown in box 426. Additionally, if the location is not a high-ranking potential work location, processor 114 can abort the work location marking process (as shown in box 428).

[0065] Similar to the marking of primary parking locations as described above, processor 114 can analyze and mark the vehicle's charging locations (or charger 110), such as... Figure 4A and Figure 4B As depicted in the text and described below.

[0066] Processor 114 can first calculate a charging cluster from vehicle charging events based on historical charging information, as shown in box 430. Processor 114 can also track the charger level of all charging events occurring at the charging cluster (as shown in box 432), and if no Level 3 charging has occurred, mark the charger as an AC charger (as shown in box 434), and if Level 3 charging has occurred, mark the charger as a DC charger (as shown in box 436).

[0067] Processor 114 can also analyze charging cluster data (as shown in box 438) and correlate it with data included in the public charger database (as shown in box 440). If a match is found based on this correlation, processor 114 can tag public / private chargers based on access type (as shown in box 442). Alternatively, if no match is found, processor 114 can track different vehicle accesses at the charging cluster (as shown in box 444) and tag the charger as a residential charger if the charger is located in a residential geographic area and vehicle 102 makes fewer than 5 different accesses to the charger (as shown in box 446). Alternatively, processor 114 can tag the charger as not being in the public charger database (as shown in box 448).

[0068] In this way, processor 114 can tag parking locations and chargers 110 (or charging locations) associated with vehicle 102 based on the vehicle's historical trip and charging information. Utility power companies and / or charger management companies can use such tagging information for multiple vehicles to optimize the charging experience for vehicle users (e.g., by installing more chargers in geographic areas where many "primary locations" for vehicles exist).

[0069] Vehicle 102 and System 104 implement and / or perform the operations described herein in accordance with the owner's manual and safety guidelines. Furthermore, any actions taken by the vehicle user shall comply with all rules specific to the location (e.g., federal, state, national, city, etc.) and operation of Vehicle 102. Any notices / recommendations provided by Vehicle 102 or System 104 shall be considered advice and followed solely in accordance with any rules specific to the location and operation of Vehicle 102.

[0070] Figure 5 A flowchart illustrating an example method 500 for optimizing vehicle charging based on the vehicle's primary location, according to this disclosure, is shown. Further description can be made with reference to the preceding figures. Figure 5 The following process is exemplary and is not limited to the steps described below. Furthermore, alternative embodiments may include more or fewer steps than shown or described herein, and may include these steps in a different order than that described in the following example embodiments.

[0071] Method 500 begins at step 502. At step 504, method 500 may include having processor 114 determine a primary location associated with vehicle 102 from a plurality of locations 108 based on historical trip information and historical charging information. At step 506, method 500 may include having processor 114 determine real-time utility power demand in a geographic area including the primary location when vehicle 102 is at the primary location.

[0072] At step 508, method 500 may include having processor 114 compare real-time utility electricity demand with a predefined demand threshold. At step 510, method 500 may include having processor 114 perform a predefined action when the real-time utility electricity demand exceeds the predefined demand threshold. Examples of the predefined actions are described below.

[0073] Method 500 may end at step 512.

[0074] In the foregoing disclosure, reference has been made to the accompanying drawings, which form a part of the foregoing disclosure, illustrating specific embodiments in which the present disclosure may be practiced. It should be understood that other embodiments and structural changes may be utilized without departing from the scope of the present disclosure. References to “an embodiment,” “embodiment,” “example embodiment,” etc., in this specification indicate that the described embodiment may include specific features, structures, or characteristics, but each embodiment may not necessarily include said specific features, structures, or characteristics. Furthermore, such phrases do not necessarily refer to the same embodiment. Moreover, when features, structures, or characteristics are described in connection with embodiments, those skilled in the art will recognize such features, structures, or characteristics in conjunction with other embodiments, whether explicitly described or not.

[0075] Furthermore, where appropriate, the functions described herein may be performed by one or more of the following: hardware, software, firmware, digital components, or analog components. For example, one or more application-specific integrated circuits (ASICs) may be programmed to perform one or more of the systems and programs described herein. Certain terms are used throughout the specification and claims to refer to specific system components. As those skilled in the art will appreciate, components may be referred to by different names. This document is not intended to distinguish between components with different names but identical functions.

[0076] It should also be understood that the term "example" as used herein is intended to be non-exclusive and non-restrictive in nature. More specifically, the term "example" as used herein refers to one of several examples, and it should be understood that there is no undue emphasis or preference on the particular example described.

[0077] Computer-readable media (also known as processor-readable media) include any non-transitory (e.g., tangible) medium that contributes to providing data (e.g., instructions) that can be read by a computer (e.g., by the computer's processor). Such media can take many forms, including but not limited to non-volatile and volatile media. Computing devices may include computer-executable instructions, wherein the instructions can be executed by one or more computing devices (such as those listed above) and stored on a computer-readable medium.

[0078] Regarding the processes, systems, methods, heuristics, etc., described herein, it should be understood that although the steps of such processes, etc., are described as occurring in a certain ordered order, such processes can be practiced by performing the described steps in a different order than that described herein. It should also be understood that some steps may be performed simultaneously, other steps may be added, or some steps described herein may be omitted. In other words, the description of processes herein is provided for the purpose of illustrating various embodiments and should in no way be construed as limiting the claims.

[0079] Therefore, it should be understood that the above description is intended to be illustrative rather than restrictive. Many embodiments and applications beyond the examples provided will become apparent upon reading the above description. The scope should not be determined by reference to the above description, but rather by reference to the appended claims and the full scope of their equivalents. It is anticipated and expected that the techniques discussed herein will evolve in the future, and the disclosed systems and methods will be incorporated into such future embodiments. In conclusion, it should be understood that modifications and changes are possible with this application.

[0080] Unless explicitly indicated otherwise herein, all terms used in the claims are intended to be given their ordinary meaning as understood by one skilled in the art as described herein. Specifically, unless the claims explicitly limit the recitation to the contrary, the use of singular articles such as “a,” “the,” or “the” should be interpreted as one or more of the elements indicated by the recitation. Unless otherwise specifically stated or otherwise understood in the context of use, conditional language such as, in particular, “can,” “may,” “may,” or “may” is generally intended to express that some embodiments may include certain features, elements, and / or steps, while other embodiments may not include certain features, elements, and / or steps. Therefore, such conditional language is generally not intended to imply that one or more embodiments require each feature, element, and / or step in any way.

[0081] According to an embodiment, the predefined action includes at least one of the following: transmitting a command signal to the vehicle to cause the vehicle to autonomously move to a second location different from the primary location; outputting a first notification including a request to move the vehicle to the second location; outputting a second notification including one or more incentives to be provided to the vehicle user when the vehicle user moves the vehicle to the second location; outputting a third notification including a request to charge the vehicle at the primary location at the current time; or outputting a command signal to the vehicle plugged in at the primary location to automatically stop charging during a window of high energy demand and resume charging outside the window of high energy demand.

[0082] According to an embodiment, the predefined action includes outputting a notification to a server associated with a charger management company, wherein the notification includes a request to install one or more new chargers at the main location.

[0083] According to an embodiment, the processor is further configured to: obtain user input associated with the home location of the vehicle; associate the primary location with the home location based on the user input; and mark the primary location as the home location when the primary location matches the home location.

[0084] According to the present invention, a method includes: a processor determining a primary location associated with a vehicle from a plurality of locations based on the vehicle's historical trip information and historical charging information, wherein the vehicle has historically visited the plurality of locations; when the vehicle is located at the primary location, the processor determining a real-time utility power demand in a geographic area including the primary location; the processor comparing the real-time utility power demand with a predefined demand threshold; and when the real-time utility power demand is greater than the predefined demand threshold, the processor performing a predefined action.

[0085] According to the present invention, a non-transitory computer-readable storage medium is provided having instructions stored thereon, the instructions, when executed by a processor, causing the processor to: determine a primary location associated with the vehicle from a plurality of locations based on the vehicle's historical trip information and historical charging information, wherein the vehicle has historically visited the plurality of locations; determine real-time utility power demand in a geographic area including the primary location when the vehicle is located at the primary location; compare the real-time utility power demand with a predefined demand threshold; and perform a predefined action when the real-time utility power demand is greater than the predefined demand threshold.

Claims

1. A system comprising: A transceiver configured to receive historical trip information and historical charging information associated with a vehicle; as well as Processor, the processor being configured to: Based on the historical trip information and the historical charging information, a primary location associated with the vehicle is determined from multiple locations, wherein the vehicle has historically visited the multiple locations; When the vehicle is located at the primary location, determine the real-time utility power demand in the geographic area including the primary location; Compare the real-time utility electricity demand with a predefined demand threshold; as well as A predefined action is executed when the real-time utility electricity demand exceeds the predefined demand threshold.

2. The system of claim 1, wherein the transceiver receives the historical trip information and the historical charging information from the server.

3. The system of claim 1, wherein the historical trip information includes location information of the vehicle at the plurality of locations where it has been parked in the past, a count of the number of times the vehicle has been parked at each location, and the duration of the vehicle's parking at each of the plurality of locations.

4. The system of claim 3, wherein the location information of the plurality of locations is identified based on historical Global Positioning System (GPS) information associated with the vehicle.

5. The system of claim 1, wherein the historical charging information includes charging location information of one or more charging locations where the vehicle was historically charged from the plurality of locations, a count of the number of times the vehicle was charged at each charging location, and the charging duration of the vehicle at each of the one or more charging locations.

6. The system of claim 1, wherein the processor is further configured to determine a primary parking location associated with the vehicle based on the historical trip information, and wherein the primary parking location is the location where the vehicle has been parked for the longest duration or the highest number of times in history.

7. The system of claim 1, wherein the processor is further configured to determine a primary charging location associated with the vehicle based on the historical charging information, and wherein the primary charging location is the location where the vehicle has historically reached the longest charging duration or the highest number of charging attempts.

8. The system of claim 1, wherein the historical trip information and the historical charging information associated with the vehicle are for a predefined historical duration.

9. The system of claim 8, wherein the processor is further configured to: Based on the historical travel information, determine one or more first locations from the plurality of locations where the parking frequency associated with the vehicle is greater than a predefined threshold; and The primary position is determined from the one or more first positions.

10. The system of claim 9, wherein the predefined threshold is once a week.

11. The system of claim 9, wherein the processor is further configured to: Based on the historical travel information, determine the first total duration at which the vehicle is parked at each of the one or more first locations; Based on the historical travel information, determine the first count of the vehicle being parked at each of the one or more first locations; as well as The primary parking confidence level associated with each of the one or more first locations is determined based on the first total duration and the first count.

12. The system of claim 11, wherein the processor is further configured to: When the predefined historical duration is greater than the predefined duration threshold, a second total duration for which the vehicle is charged at each of the one or more first locations is determined based on the historical charging information. When the predefined historical duration is greater than the predefined duration threshold, a second count of the number of times the vehicle is charged at each of the one or more first locations is determined based on the historical charging information. as well as The primary plugging confidence level associated with each of the one or more first locations is determined based on the second total duration and the second count.

13. The system of claim 12, wherein the processor is further configured to: A primary confidence level associated with each of the one or more first locations is calculated based on at least one of the primary parking confidence level or the primary plugging confidence level for the corresponding first location; and The primary position is determined from the one or more first positions based on the primary confidence level associated with each of the one or more first positions.

14. The system of claim 13, wherein the processor is further configured to: A first potential candidate position is determined from the one or more first positions such that the major confidence level associated with the first potential candidate position is the highest among the major confidence levels associated with the one or more first positions; and The first potential candidate location is selected as the primary location for the vehicle.

15. The system of claim 14, wherein the processor is further configured to: A second potential candidate position is determined from the one or more first positions such that the major confidence level associated with the second potential candidate position is the second highest among the major confidence levels associated with the one or more first positions; Based on the historical travel information, calculate a first difference between the number of times the vehicle is parked at the first potential candidate location and the number of times the vehicle is parked at the second potential candidate location; Based on the historical travel information, a second difference is calculated between the total duration of the vehicle parked at the first potential candidate location and the total duration of the vehicle parked at the second potential candidate location; as well as When the first difference is greater than a first predefined threshold and the second difference is greater than a second predefined threshold, the first potential candidate position is selected as the primary position for the vehicle.

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