Smart energy distribution methods and systems for electric vehicle charging

A power management system can smartly allocate the available power at a location to support more electric vehicles than would otherwise be possible. Power managers can intelligently allocate that power based on the real-time needs of vehicles. A smart energy distribution system can estimate each vehicle's current charge level and use such information to efficiently provide electric vehicle charging. The system can respond dynamically to vehicle charge levels, current readings, and/or electrical mains readings, allocating more current where it is needed. The charger profiles can include historic charge cycle information, which can be analyzed under a set of heuristics to predict future charging needs. A local electric vehicle charging mesh network can be provided, which transmits data packets among short-range transceivers of multiple power managers. The local electric vehicle charging mesh network can be connected to a remote server via a cellular connection. The power managers and the local electric vehicle charging mesh network can intelligently allocate power to multiple electric vehicles.

FIELD

This disclosure relates to electric vehicles, and, more particularly, to smart energy distribution methods and systems for electric vehicle charging allocation techniques and multi-level garage electrical vehicle charging infrastructure.

BACKGROUND

The adoption of electric vehicles, plug-in hybrid electric vehicles, and the like, continues at a rapid pace. The charging infrastructure is still in its infancy and many challenges remain including scaling, efficiency, and cost barriers. Conventional charging and energy distribution systems lack any significant level of built-in intelligence, and as a result, the methods used for charging electric vehicles are usually wasteful and inefficient.

Moreover, as the deployment of electric vehicles increases, the charging infrastructure must be adapted to meet demand. Multi-level parking spaces used in apartment complexes, shopping malls, downtown parking garages, and the like, suffer from a variety of unique problems such as the coordination of charging devices among the various levels. Many such parking spaces are constructed of dense materials such as cement and steel, which impede conventional wireless networking solutions. This in turn diminishes the coordination and communication of different components of a charging system or network, and consequently, the intelligence of such conventional systems are either difficult to implement, too costly to install, or simply impossible.

Accordingly, a need remains for improved methods and systems for efficiently and intelligently distributing energy to electric vehicles. Embodiments of the invention address these and other limitations in the prior art.

The foregoing and other features of the invention will become more readily apparent from the following detailed description, which proceeds with reference to the accompanying drawings.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to embodiments of the inventive concept, examples of which are illustrated in the accompanying drawings. The accompanying drawings are not necessarily drawn to scale. In the following detailed description, numerous specific details are set forth to enable a thorough understanding of the inventive concept. It should be understood, however, that persons having ordinary skill in the art may practice the inventive concept without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments.

It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first electric vehicle could be termed a second electric vehicle, and, similarly, a second electric vehicle could be termed a first electric vehicle, without departing from the scope of the inventive concept.

Reference is often made herein to “electric vehicles.” It will be understood that such vehicles can include plug-in hybrid vehicles, pure electric vehicles, or any one of a variety of vehicles that operate or move using at least some electricity. The term “control signal” as referred to herein can be a “pilot signal,” or other suitable control signal. The term “pilot signal” as referred to herein can be a low voltage connection that is used to control a level of current draw that the electric vehicle requests or is allowed to request.

Embodiments of the invention include a power management system that smartly allocates the available power at a location to support more electric vehicles than would otherwise be possible. When a power manager has the information about the amount of available power available on a given supply, it can intelligently allocate that power based on the real-time needs of vehicles. By monitoring the current draw on each electric vehicle using a current sensor or by accessing the electric vehicle's state of charge through an API accessed through a remote access or server network (which can include information about user history or input, real-time data, and/or historical data), a smart energy distribution system disclosed herein can estimate each vehicle's current charge level and use this information to provide the minimum amount of needed current with or without a buffer to the electric vehicle. This system works with one or many electric vehicles using the charging system.

Such approach allows a site electrical capacity to be allocated efficiently and uses a low voltage signal to have the electric vehicles regulate charge levels internally, as further explained below. The system can respond dynamically to vehicle charge levels, current readings, and/or electrical mains readings, allocating more current where it is needed. Cycle point and/or charger profiles for individual electric vehicles can be determined and/or stored. The charger profiles can include historic charge cycle information, which can be used and analyzed under a set of heuristics to predict future charging needs, including expected time-of-day and charge level approximations.

A local electric vehicle charging mesh network can be provided, which transmits data packets among short-range transceivers of multiple power managers that are configured to be part of the local electric vehicle charging mesh network. The local electric vehicle charging mesh network can be connected to a remote server via a cellular connection, which is disposed at a location associated with a parking structure that provides a sufficient and/or reliable cellular reception. The power managers and the local electric vehicle charging mesh network can intelligently and unevenly allocate power to multiple electric vehicles using the local electric vehicle charging mesh network. The remote server can provide analytical information about the local electric vehicle charging mesh network, the power managers, the electric vehicles, and the like, as further described in detail below. The remote server can be located in a geographical location entirely different from the parking structure, such as at a control center in another city, state, or country. Alternatively, the remote server can be located proximate to or within the parking structure. In this embodiment, the remote server is “remote” to the mesh network.

FIG. 1illustrates a smart energy distribution system100for providing smart energy distribution via an intelligent control signal (e.g.,118) in accordance with various embodiments of the present invention. The smart energy distribution system100can include electric vehicles105, current sensors130, pilot signals118, insulated and/or isolated connectors110, a remote server145, a database of user identifiers (IDs)155, control logic160, power managers (e.g.,115,120and125), and a power source140. Alternatively or in addition, the control logic160can be localized to each power manager. For example, the power manager115can include control logic135. One or more of the power managers115,120, and125can be connected to the power source140. The one or more power managers115,120, and125can use a pilot signal118to regulate the amount of power an electric vehicle105is allowed to draw. The pilot signals118supplied to the different vehicles105can be varied based on the control logic160, which can optionally be localized (e.g.,135) and/or modified by information received over a network connection150. The network connection150can include or otherwise be connected to, for example, the Internet. The information received over the network connection150can include real-time information about energy demand elsewhere at one or more other locations (not shown).

The power managers115,120, and/or125can each include or be associated with a microprocessor (e.g.,165), a pilot signal generator (e.g.,170), an electric vehicle connector cord (e.g.,175), and/or a wired or wireless communication connection (e.g.,180) to interface with other power managers and/or with a network. The power managers115,120, and/or125can determine the state of charge (e.g.,185) of one or more of the electric vehicles105(e.g., the approximate point in the electric vehicle's charge cycle). It will be understood that while three electric vehicles105are shown, any suitable number of electric vehicles can be used with or otherwise charged by the smart energy distribution system100.

Using the approximate state of charge185of an electric vehicle105and the pilot signal118, charge between multiple power managers (e.g.,115,120, and125) can be managed using the control logic (e.g.,160and/or135) to have the electric vehicles105internally regulate how much power each will draw from the power source140. In other words, the power managers (e.g.,115,120, and125) can generate and/or control the pilot signal118for each electric vehicle, which can cause each electric vehicle105to limit and/or alter the amount of power that it will draw over time.

The information about the electric vehicle's state of charge185(e.g., point in its charge cycle) can be stored in the remote server145and/or accessed via the network150. The power managers (e.g.,115,120, and125) can use pilot signals118to control the electric vehicles' internal control of current draw to regulate amperage so that the total amperage for a given charging location does not exceed the amount of power available at the given charging location. The power managers (e.g.,115,120, and125) can allocate available power to the electric vehicles105using the reading from current sensors130associated with each of the corresponding power managers (e.g.,115,120, and125) and electric vehicles105to predict the appropriate allocation of power to each electric vehicle105. The system can include a user input device190, which can allow a user (e.g., driver of the electric vehicle105) to make a request for charging in which the request causes the corresponding power manager (e.g.,115,120, and125) to maximize mileage for the electric vehicle105, minimize energy costs for the electric vehicle105, and/or increase charging speed for the electric vehicle105.

The smart energy distribution system100can include a combination of Electric Vehicle Service Equipment (EVSE) and energy management device (e.g., power managers115,120, and125), which can include or otherwise interface with an intelligent monitoring apparatus (e.g.,175and110) that includes the connector (e.g.,110). The connector110can include one or more safety components for isolating high power from the user of the electric vehicle105. The power managers (e.g.,115,120, and125) can communicate with the electric vehicles105using a low voltage pilot signal118. The smart energy distribution system can include a connector110having one or more safety components that can dynamically regulate power management through communication with combination EVSE power manager devices (e.g.,115,120, and125) directly, indirectly, and/or over a network. The method of communication between EVSE can include wireless, locally, connected, wired, Ethernet, mesh network, full on/off timed system, and/or any suitable IP connected device.

The power managers (e.g.,115,120, and125) can communicate with each other and/or with the remote server145to prioritize one electric vehicle105over another electric vehicle105for charging. The prioritization can be based on user inputs via the user input device190, state of charge information185, a maximum rated charge level195of an installation, and/or a current sensor reading from the current sensor130. The power managers (e.g.,115,120, and125) can communicate with each other and/or with the remote server145to generate a prioritization and average distribution198. The prioritization and average distribution198can be regulated by customer input and rankings. The prioritization and average distribution198can be regulated by predictive time slicing gathered from past time slicing. The prioritization and average distribution198can be regulated by adaptive learning logic, which can improve the predications and prioritizations.

The prioritization and average distribution198can be regulated by how much the user wants to pay. The user can input via the user input device190how many miles desired from a given charging session and/or prioritize by a request to have the vehicle fully charged. The prioritization and average distribution198can be regulated by the control logic (e.g.,160and/or135) to provide a feedback loop. The feedback loop can provide a rate schedule for an electrical utility company142. The electrical utility company142can recommend what rate schedule the charging location can use including suggestions for a cheapest rate.

FIG. 2illustrates a power balancing system200from a limited power supply or supplies205(hereinafter referred to as power supply205) in accordance with embodiments of the present invention. For a given charging location (such as a multi-car garage, series of parking spaces, apartment building, or the like) associated with the power supply205, there is a given amount of installed power (e.g., installed Kilowatts (KW)) that is available. Different percentages (e.g.,215,220, and225) of this available pool205can be allocated to multiple electric vehicles (e.g.,230,235, and240), respectively. According to embodiments of the invention disclosed herein, the percentages can be dynamically changed and controlled. For example, the power managers (e.g.,115,120, and125ofFIG. 1) and/or the remote server145(ofFIG. 1) can dynamically change and control the different percentages of the available pool of power205that are allocated to each of the electric vehicles (e.g.,230,235, and240). The different percentages in the aggregate210are equal to 100% of the allocable power, which may take into account a buffer as further described below. Each allocation percentage can be the same as or different from another allocation percentage from among the allocation percentages.

FIG. 3illustrates a block diagram of system300including a power manager305and associated power regulation components (e.g.,320and380) in accordance with embodiments of the present invention. The power manager305can receive information from a current sensor380, and together with the control logic section320, regulate the charging power of an electric vehicle360. Although the control logic section320is shown as separate from the power manager305, it will be understood that the power manager305can include the control logic section320. The electric vehicle360can be allowed to draw using a pilot signal340. In other words, the control logic section320can adjust a signal level of the pilot signal340, thereby controlling the maximum charge level of the electric vehicle360. The current sensor380can provide a feedback loop for the power manager305and/or the control logic section320for further adjusting of the pilot signal340. The electric vehicle charge level of the electric vehicle360can therefore be controlled.

FIG. 4shows a flow diagram400illustrating a technique for providing smart energy distribution via an intelligent control signal in accordance with embodiments of the present invention. The technique can begin at415, where an available and/or installed maximum power and/or Amperes (hereinafter referred to as “amps”) can be determined. The available and/or installed maximum power and/or amps can be associated with a particular location such as a parking garage, apartment complex, parking lot, or the like. The flow can proceed to405where a determination can be made whether power is requested by a user (e.g., by an electric vehicle). If no power is requested, then there need not be any smart resource allocation, and therefore, the flow proceeds to no smart resource allocation at410. Otherwise, if power is requested, then the system can initially distribute power to the electric vehicles equally at420. The power may be distributed according to the maximum amount of installed power (e.g., available kilowatts (KW)) and/or amps for the location, with or without a buffer, as further described below. The power may be distributed to the electric vehicles based on the vehicle's rated acceptable or maximum levels.

At425, the current sensor (e.g.,380ofFIG. 3) can be periodically checked to determine whether the amount of power allocated exceeds the real current that the vehicle is drawing. At430, a determination can be made whether the amount of power distributed to the vehicles should be reallocated. In other words, the amount of current a vehicle is drawing over a period of time can be used to predict the rest of a charging cycle, as further explained below. If the amount of power distributed to the electric vehicles is to be reallocated, the flow can proceed to432, where the energy can be intelligently and/or unevenly allocated among the electric vehicles, and then to425for additional checking of the current sensor for excess allocation. Otherwise, the flow proceeds along the NO path to end the technique. It will be understood that the steps and elements ofFIG. 4need not occur in the order shown, but rather, can occur in a different order or with intervening steps, or without some of the steps.

FIG. 5illustrates a chart500and associated technique for smart energy distribution to five vehicles in accordance with embodiments of the present invention. As can be seen inFIG. 5, five electric vehicles (V1, V2, V3, V4, and V5) are shown. It will be understood that the number of five electric vehicles is exemplary, and any suitable number of electric vehicles can be associated with the inventive techniques described herein. In this example, it is assumed that the given amount of installed amps for the charging location is 100 amps (e.g., a circuit rated at 100 amps). The technique involves a series of steps, denoted by505through540. The number of amps that are intelligently allocated are numerically shown in the five columns associated with vehicles V1through V5. The power managers (e.g.,305ofFIG. 3) can allocate an amount of allocable power among the vehicles V1through V5. The allocable amount of power can be a total amount of installed power for a given location minus a buffer. The power managers can intelligently allocate the allocable amount of power according to a set of heuristics.

At505, the user request indicates whether a person is trying to charge their electric vehicle at the present moment. The request can be made by an RFID signal or other suitable wired or wireless method. In this case, four of the five vehicles (i.e., V1, V2, V3, and V4) have requested power. V5is fully charged and therefore is not requesting power at this time.

At510, the defined charge level of each electric vehicle is shown. Each electric vehicle in this case takes a maximum of 50 amps to charge. Because V5is already charged it requires 0 amps to charge. The 100 amp circuit cannot charge four vehicles at once with 50 amps each because the circuit only has 100 total amps of charging capacity, and four times 50 amps would be 200 amps, which exceeds the 100 total amps of capacity. Pertaining to515, where time (t)=0, each charging system can simultaneously supply 25 amps from the 100 amp circuit to the four electric vehicles without exceeding the 100 amp installed limit, without taking into account any kind of buffer.

As shown at520, to comply with electric governmentally imposed codes, each vehicle can receive 20 amps, for a total of 80 amps. V5didn't request charging, so 0 amps are allocated to it. The remaining 20 amps (i.e., 100 minus 80) are not allocated to conform with government code. The remaining 20 amps provide a buffer between the total installed amps and the amount of amps that are intelligently allocated to the various electric vehicles.

At525, time (t)=1, a current sensor can read that V2and V3are charging at a high level. This information can be accessed through a charge level application specific interface (API). By way of example, V2and V3can request priority charging, and therefore, can be charged at a higher priority. The higher priority charging can mean receiving a charge earlier in time and/or at a higher power level.

At530, time (t)=2, vehicles V1and V4are nearing the end of the charge cycle, and so V1and V4are allocated five amps each. The vehicles V2and V3are not at the end of the charge cycle, and therefore vehicles V2and V3can be allocated 15 more amps each, up to a total of 35 amps each.

At535, time (t)=3, another current draw reading can be performed, and it can be determined from the current draw reading that V1and V4are nearly finished charging. V2and V3continue to be allocated 35 amps each to ensure that electrical code requirements are still met while allowing V1and V4to safely finish charging.

At540, time (t)=4, yet another current drawing reading can be performed, thereby determining that V1and V4are entirely finished charging. Therefore, V2and V3can be allocated an increased charging level of 40 amps each, still maintaining compliance with the electrical code requirements. In some embodiments, V2and V3are allocated their maximum charging level assuming that the code requirements can still be met.

The power managers (e.g.,305ofFIG. 3) can intelligently allocate an allocable amount of power among the electric vehicles for charging the electric vehicles. The allocable amount of power can be a total amount of installed power for a given location minus a buffer. The power managers can intelligently and unevenly allocate the allocable amount of power among the electric vehicles according to a set of heuristics. For example, the power managers can allocate, during a first time period, an equal fraction of the allocable amount of power to each of the electric vehicles. The power managers can allocate, during a second time period, a first fraction of the allocable amount of power to a first subset of the electric vehicles. The power managers can allocate during the second time period, a second fraction different from the first fraction of the allocable amount of power to a second subset of the vehicles. The power managers can allocate, during a third time period, a third fraction different from the first and second fractions of the allocable amount of power to the first subset of electric vehicles. The power managers can allocate, during a fourth time period, a fourth fraction different from the first, second, and third fractions of the allocable amount of power to the second subset of the electric vehicles, and so forth.

FIG. 6shows a flow diagram600illustrating another technique for providing smart energy distribution via an intelligent control signal in accordance with embodiments of the present invention. This technique involves a method of using the real time or recent charge estimates, determined either from a current sensor (e.g.,380ofFIG. 3), learning algorithm (e.g., within control logic160and/or135ofFIG. 1), and/or an API, to access network based vehicle data, for example via network150(ofFIG. 1), and use such data to allocate power to the electric vehicle or vehicles.

The technique can begin at605with a determination of whether there are user requests. If there are no user requests at605, then no smart resource allocation needs to be made, and therefore the flow proceeds to615. Otherwise, if there are user requests at605, then the flow can proceed to610where a determination can be made whether there are too many users. The determination of whether there are too many users can be a determination of whether the charging and/or power demand associated with the number of electric vehicles present exceeds the total installed power and/or amps, taking into account any buffer. If YES, meaning that the charging need exceeds what is available (e.g., the total requested amps exceeds the total installed amps minus the buffer), then the flow can proceed to620, where charge cycle real-time demand estimates can be determined. Otherwise, if NO, meaning that the charging need does not exceed what is available (e.g., the total requested amps is less than the total installed amps minus the buffer), then the flow can proceed to615where no smart allocation of resources is needed.

At625, the estimates can be used to allocate minimum estimated need to each vehicle. At630, power is allocated to the vehicles according to the minimum estimated need to each vehicle. At635, a determination can be made whether power should be reallocated. If YES, the flow can return to605for further determinations and further charging. It will be understood that the steps and elements ofFIG. 6need not occur in the order shown, but rather, can occur in a different order or with intervening steps, or without some of the steps.

FIG. 7illustrates a graph demonstrating the regulation of the vehicle charging in accordance with embodiments of the present invention. The graph shows a run check cycle700. The current reading720from the current sensor (e.g.,380ofFIG. 3) can be used to regulate the vehicle charging to a lower maximum without inhibiting an electric vehicle's charge time or charging cycle. As shown in this example, there are two pilot controlled maximum charge levels740, which represent two different maximum charge levels740for two different times. In other words, as the charging of the electric vehicle progresses along the current reading curve720, the pilot signal controlled max charge level740can be progressively lowered. In some embodiments, the pilot signal controlled max charge level740can be incrementally lowered as the charging of the electric vehicle progresses. Alternatively, the pilot signal controlled max charge level740can be continuously lowered as the charging of the electric vehicle progresses. The power managers (e.g.,305ofFIG. 3) can collectively and/or individually control the pilot signal controlled max charge level over time for each electric vehicle being charged.

FIG. 8illustrates a block diagram of a multi-circuit multi-parking-level electric vehicle charging system800, including a local vehicle charging mesh network880in accordance with embodiments of the present invention. It is quite common in large apartment complexes or city-based parking garages to have multiple parking levels. The parking levels are often separated by thick concrete floors and walls, which can impede the transmission of wireless signals. Power managers (PMs) can be located on each parking level. Each PM can be incorporated into Electric Vehicle Supply Equipment (EVSE) or otherwise be separate from and/or connected to an EVSE.

For example, PM820can be located on level1, PM815and PM810can be located on level2, and PM805can be located on level N. It will be understood that any suitable number of PMs and parking levels can be part of the electric vehicle charging mesh network800. A local short-range wireless electric vehicle charging mesh network880can interconnect the PM805, the PM810, the PM815, and the PM820. In other words, the local vehicle charging mesh network880can interconnect the short-range wireless transceivers of the PM805, the PM810, the PM815, and the PM820. Each of the PMs can receive, process, retransmit, and/or store data packets that are transmitted on the local vehicle charging mesh network880by each of the PMs. In other words, each of the PMs can receive, process, retransmit, and/or store all data packets that are transmitted on the local vehicle mesh network880. It will be understood that any suitable number of parking levels and PM units can be included in the local short-range wireless electric vehicle charging mesh network880. The effective reach of each short-range transceiver (e.g.,840,845,850, and855) of each PM is lengthened, since connection to one node is sufficient to access the entire network. In other words, each short-range wireless transceiver (e.g.,840,845,850, and855) within the local electric vehicle charging mesh network880“sees” all packets that are transmitted among the various nodes within the network. Thus, the reach of each node (i.e., PM) is expanded.

This technique is particularly useful in the multi-level garage application because as mentioned above, the natural conditions of these environments prohibit the typical range of wireless signals. One of the PMs, e.g. PM805, can include a long-range transceiver such as a cellular transceiver835to connect the short-range wireless electric vehicle charging mesh network880to the Internet via a cellular connection885. The cellular connection885can connect the cellular transceiver835to a cellular or radio tower860, which can be connected to the Internet. The PM805can be situated in a spot that is suitable for cellular reception, which can be, for example, the top level of a multi-level parking structure. The long-range transceiver835of the PM805can connect the local vehicle charging mesh network880to the remote server145via the cellular connection885. The remote server145can provide analytical information about the local vehicle charging mesh network880, the electric vehicles associated with the vehicle charging mesh network880, the power managers associated with the vehicle charging mesh network880, the information stored thereon, and so forth.

Parking spaces are constructed of dense materials such as cement and steel, which impede conventional wireless networking solutions. This in turn diminishes the coordination and communication of different components of a conventional charging system or network. The long-range transceiver835can be located on a level of a parking structure that is higher in elevation than other levels, or at the highest level, so that a reliable connection can be made to the cellular tower860via the cellular connection885. The long-range transceiver835can thus connect the local vehicle charging mesh network880to the remote server145via the cellular connection885. Referring toFIG. 8, the level N of the parking structure can be higher in elevation than the level2of the parking structure, and the level2of the parking structure can be higher in elevation than the level1of the parking structure.

Each PM (e.g.,805,810,815, and820) can be associated with a given circuit (e.g.,825and830). For example, as shown inFIG. 8, PM810, PM815, and PM820can be associated with circuit830, whereas PM805can be associated with circuit825. It will be understood that any suitable number of PMs can be associated with a given circuit. It will be understood that any suitable number of circuits can be associated with a particular location. In some embodiments, the association can also span multiple parking levels (e.g., PMs located on levels1and2are associated with circuit830). Each PM can include control logic (e.g.,135ofFIG. 1) that makes it aware of which circuit it is associated with. The PM can be assigned a circuit or breaker identifier (ID) (e.g.,890) using a dip switch, a configurable setting such as a memory register, or the like. The local electric vehicle charging mesh network880can be collectively aware of which PMs are associated with which circuits, and can allocate electric vehicle charging resources and power levels accordingly.

The local electric vehicle charging mesh network880can record and/or log system change events898such as current levels of charging, electric vehicle disconnections, electric vehicle connections, charging completing, charging starting, charging levels, and the like. The system change events898can be stored on each PM, such as in storage unit895of PM810. The change events can include a current level of charging event for a particular electric vehicle, an electric vehicle disconnection event from a particular PM from among the various PMs, and/or an electric vehicle connection event to a particular PM from among the various PMs. The change events can include a charge completing event for a particular electric vehicle and a charge starting event for the particular electric vehicle.

The system change events898can be associated with time and stored as a history of events, which can be used to predict future events based on a set of heuristics. In some embodiments, the history of events for each PM can be stored on each PM. In some embodiments, the history of events for a particular PM can be stored only for the particular PM. The local electric vehicle charging mesh network880can include a learning logic section (e.g.,888) to learn from the history and predict future behavior and future needs of EVs. Each PM can include the learning logic section (e.g.,888) to learn the history for that particular PM, for each of the PMs, and/or for the associated EVs. The learning logic section888can formulate or refine heuristics892. The PMs can track individual electric vehicles using a vehicle identifier876, such as radio frequency ID (RFID) tag and/or a near-field communication (NFC) tag. The PMs can track the individual electric vehicles via the local electric vehicle charging mesh network880. Each PM can access the stored history (e.g., stored on895) and apply the heuristics892to predict how much charge a particular electric vehicle will need at a particular time of day, and/or based on a particular day. Charging can be prioritized based on a user's usual arrival time, connection time, charging time, disconnection time, and/or time of leaving. Because all of the PMs have access to all of the data packets, change events, and stored history of the local vehicle charging mesh network880, a particular electric vehicle can plug into any of the PMs, and the prediction techniques can still be used to improve the charging experience of the particular electric vehicle. The PMs can allocate among themselves the available power for each electric vehicle based at least on immediate demand and/or the heuristics892. The PMs can provide a predictive readout of total charge time (e.g., current draw, charge length, position in queue, and the like) based at least on the heuristics892. The PMs can reconfigure the level of charge provided to each electric vehicle based on the total power available for a given circuit. Because reconfiguring is an expensive operation in terms of time and/or electric vehicle charging protocol limitations, the amount of reconfiguring needed can be reduced by relying on the predictive heuristics892.

For example, if a particular electric vehicle is known to only trickle charge at a particular time of day, then a trickle charge can be applied from the start, i.e., at the time the electric vehicle plugs in and requests a charge. By way of another example, a PM might determine that at 2 PM on weekdays a particular electric vehicle will need a full charge. By way of yet another example, just because an electric vehicle is first to plug into a given PM associated with a given circuit, that does not necessarily mean that that electric vehicle receives a full or maximum charging power level, but rather, based on the heuristics892, that electric vehicle may receive from the start a reduced level of charging power.

The PMs can determine where each electric vehicle is in the charging cycle and adjust current and/or power levels up or down, using for example, the pilot signal described above. The charging cycle data can be represented and stored on895and/or the remote server (e.g.,145ofFIG. 1) as graphs, logs, change event lists, or the like. The PMs can determine whether the current day is a weekday or a weekend day and adjust accordingly. The heuristics892can also be used to determine safety buffers in the charging, and can take into account history and immediate needs. For example, the heuristics892can include information regarding the maximum installed power for a given location and the built-in buffer for adhering to government code. The PMs can provide predictive information to electric vehicle owners, such as estimations of time of charge completion, charging rate, or the like. Such information including the heuristics, the graphs, the logs, the change event list, the predictive information, or the like, can be stored on in the database155of the remote server145. Electric vehicle owners can remotely access such information via a mobile device such as a smart phone or tablet (e.g.,894).

A particular PM (e.g.,805,810,815, and820) can determine when a particular electric vehicle requests and receives a charge. The particular PM can determine an amount of charge that is needed to complete the charge. The PM can analyze past charge currents or events. The PM can match the pilot signal (e.g.,340ofFIG. 3) to draw a current that is equal to a predictive current draw for a particular electric vehicle based on the heuristics892. In the event that an electric vehicle requests a “normal” maximum charging level, and the “normal” maximum charging level is unavailable due to circuit constraints, then the PM can use the heuristics892to determine a charging level that is less than the “normal” maximum charging level. The “less-than-normal” charging level can be a charge level that is less than the “normal” maximum charging level. For example, based on the heuristics892, the PM can cause the less-than-normal charging level to be used to charge the particular electric vehicle.

FIG. 9illustrates a diagram of a multi-circuit multi-parking-level apartment complex905including distributed power managers (e.g., PMs950and955) for controlling the distribution of power to electric vehicles (e.g., electric vehicle945) and to other apartment appliances (e.g., lights960) in accordance with embodiments of the present invention. It will be understood that while the term apartment complex is used with reference toFIG. 9for the sake of illustrating an exemplary embodiment, other parking structures not necessarily associated with apartment complexes are equally applicable and suitable for incorporating the various embodiments of the invention as described herein. The apartment complex905can have an electrical mains962line associated therewith. The electrical mains962can be connected to a transformer910. The transformer910can step down the voltage received over the mains962. The transformer910can be connected to an electrical disconnect unit915. The electrical disconnect unit915can be connected to a circuit panel board920. The electrical disconnect915can disconnect or connect the transformer910from or to the circuit panel board920. The circuit panel board920can include various sub-panels (e.g.,925and930). For example, the circuit panel board920can include a main panel925used for providing power to apartment appliances such as lights960, plug outlets972, or the like. Alternatively or in addition, the circuit panel board920can include one or more sub-panels930used for providing power charging to the electric vehicles945.

The one or more sub-panels930can include multiple circuits (e.g., circuit1and circuit2), with associated breakers (e.g., breaker935and breaker940) for each circuit. The circuit1can be associated with a sub-set of PMs, such as those PMs located on level N (i.e., LN) of the parking garage. The circuit2can be associated with a different sub-set of PMs, such as a portion of the PMs on level1(i.e., L1) and/or a portion of the PMs on level2(i.e., L2) of a parking garage of the complex905. A local electric vehicle charging mesh network880, as described above with reference toFIG. 8, can interconnect the PMs throughout the apartment complex905and/or the associated parking garage982including those PMs associated with charging the electric vehicles945, and those PMs (e.g.,955) associated with powering other appliances such as the lights960or via the plug outlet972.

Measurement points can be located along the chain of power supply components. For example, a measurement point can be located at965associated with the mains962. A measurement point can be located at970between the transformer910and the disconnect915. A measurement point can be located at975between the disconnect915and the circuit panel board920, and so forth. The local electric vehicle charging mesh network880(ofFIG. 8) can monitor the measurement points along this chain, and adjust the distribution of power throughout the apartment complex905responsive to the measurements. For example, the local electric vehicle charging mesh network880can monitor the aggregate amount of power available relative to the aggregate amount of power currently being consumed. The local electric vehicle charging mesh network880can automatically reconfigure an amount of power being used by each circuit within the circuit panel board920. In the case where there are more installed circuits than what the transformer910can safely support in a simultaneous fashion, the local electric vehicle charging mesh network880can cause power to disabled to certain circuits and power to be enabled to other circuits during different time periods. The local electric vehicle charging mesh network880can rank and prioritize which circuits get power and/or the level of power available to each circuit. At the individual PM level, each PM within the local vehicle charging mesh network880can determine how much power (e.g., based on a current level controlled by a pilot signal such as340ofFIG. 3) a particular electric vehicle is allowed to draw in view of the present state of the local electric vehicle mesh network880. In other words, each PM can be self-aware of the overall power usage across the network of PMs in view of the power limitations of each circuit, and in view of the power limitations of the transformer910, and make autonomous charging decisions based at least on such information. The PMs can also rely on predictive heuristics (e.g.,892ofFIG. 8) to balance the distribution of the available power among the electric vehicles and other apartment appliances.

It will be understood that even though the electric vehicle charging network is preferably a local electric vehicle charging mesh network880as described herein, the network can also be configured in a server/client arrangement and/or a master/slave arrangement.

The following discussion is intended to provide a brief, general description of a suitable machine or machines in which certain aspects of the invention can be implemented. Typically, the machine or machines include a system bus to which is attached processors, memory, e.g., random access memory (RAM), read-only memory (ROM), or other state preserving medium, storage devices and units, a video interface, and input/output interface ports. The machine or machines can be controlled, at least in part, by input from conventional input devices, such as keyboards, mice, etc., as well as by directives received from another machine, interaction with a virtual reality (VR) environment, biometric feedback, or other input signal. As used herein, the term “machine” is intended to broadly encompass a single machine, a virtual machine, or a system of communicatively coupled machines, virtual machines, or devices operating together. Exemplary machines include computing devices such as personal computers, workstations, servers, portable computers, handheld devices, telephones, tablets, etc., as well as transportation devices, such as private or public transportation, e.g., automobiles, trains, cabs, etc.

The machine or machines can include embedded controllers, such as programmable or non-programmable logic devices or arrays, Application Specific Integrated Circuits (ASICs), embedded computers, smart cards, and the like. The machine or machines can utilize one or more connections to one or more remote machines, such as through a network interface, modem, or other communicative coupling. Machines can be interconnected by way of a physical and/or logical network, such as an intranet, the Internet, local area networks, wide area networks, etc. One skilled in the art will appreciate that network communication can utilize various wired and/or wireless short range or long range carriers and protocols, including radio frequency (RF), satellite, microwave, Institute of Electrical and Electronics Engineers (IEEE) 545.11, Bluetooth®, optical, infrared, cable, laser, etc.

Embodiments of the invention can be described by reference to or in conjunction with associated data including functions, procedures, data structures, application programs, etc. which when accessed by a machine results in the machine performing tasks or defining abstract data types or low-level hardware contexts. Associated data can be stored in, for example, the volatile and/or non-volatile memory, e.g., RAM, ROM, etc., or in other storage devices and their associated storage media, including hard-drives, floppy-disks, optical storage, tapes, flash memory, memory sticks, digital video disks, biological storage, etc. Associated data can be delivered over transmission environments, including the physical and/or logical network, in the form of packets, serial data, parallel data, propagated signals, etc., and can be used in a compressed or encrypted format. Associated data can be used in a distributed environment, and stored locally and/or remotely for machine access.

Having described and illustrated the principles of the invention with reference to illustrated embodiments, it will be recognized that the illustrated embodiments can be modified in arrangement and detail without departing from such principles, and can be combined in any desired manner. And although the foregoing discussion has focused on particular embodiments, other configurations are contemplated. In particular, even though expressions such as “according to an embodiment of the invention” or the like are used herein, these phrases are meant to generally reference embodiment possibilities, and are not intended to limit the invention to particular embodiment configurations. As used herein, these terms can reference the same or different embodiments that are combinable into other embodiments.

Embodiments of the invention may include a non-transitory machine-readable medium comprising instructions executable by one or more processors, the instructions comprising instructions to perform the elements of the inventive concepts as described herein.