Procedure for selecting a charging station

Abstract

A method for selecting a charging station (50) for a respective vehicle (10), the method comprising: Determining, for the vehicle (10) in question, a charge state of a vehicle-specific direct current source (14) which is configured to supply a drive system (12) for the vehicle (10) in question with electrical energy; Determining, for the vehicle in question (10), a travel route to a destination point; Determining desired states and corresponding weighting factors for a variety of user-selectable parameters; identifying locations of a plurality of charging stations located proximal to a travel route of the vehicle (10) in question; Determining a ranking factor for the plurality of charging stations based on the desired states and corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the vehicle's own DC power source (14); Selecting one of the plurality of charging stations based on the ranking factor; and scheduling a charging reservation for the vehicle (10) in question with the selected charging station from the plurality of charging stations, wherein determining a ranking for the plurality of charging stations based on the desired states and corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the vehicle's own DC power source (14) comprises determining a plurality of ranking factors for the plurality of charging stations and executing a sorting routine of the plurality of charging stations based on the plurality of ranking factors, where each of the plurality of ranking factors is determined according to: Fi = ( S * Wc * Wt * Wd * Wd * Wpoi * Wn * Wb * We * Wr ) where: Fi represents a ranking factor for the charging station i, where i represents one of the charging stations; and S = Sort(d+c or t); or optimize for one of d, c, or t based on user preferences; d < maximum deviation from the route, cost c = {min:max} and t = estimated travel time, Wc represents a weighting factor related to the cost associated with charging station i, Wt represents a weighting factor associated with an expected waiting time associated with the charging station i, Wd represents a weighting factor associated with a deviation from the travel route associated with charging station i, Wpoi represents a weighting factor associated with a point of interest connected to the charging station i, Wn represents a weighting factor associated with a number of charging points connected to the charging station i, Wb represents a weighting factor associated with a provider preference associated with charging station i, We represent a weighting factor associated with a travel route connected to charging station i, and Wr represents a weighting factor associated with customer ratings related to charging station i.

Description

INTRODUCTION

[0001] Electric vehicles require charging, which can be done at commercial or residential charging stations. Factors associated with selecting a desired charging station include determining whether a charging station will be available in the near future or determining whether a charging station is close to a desired or convenient location. It may be beneficial to facilitate the selection and scheduling of a desired charging station based on a charging profile and travel time to reduce waiting time and / or travel distance.

[0002] DE 10 2014 001 300 A1 describes a method for controlling a hybrid drive with an electric motor and an internal combustion engine in a motor vehicle, wherein a route with at least one route section and an operating mode of the hybrid drive of the motor vehicle assigned to the route section is calculated to an entered destination and the hybrid drive is operated while the motor vehicle is traveling along the calculated route in accordance with the operating mode assigned to the route section currently being traveled, wherein the destination is entered on an operating device designed separately from the motor vehicle, after which the destination and / or at least one item of information derived from the destination is transmitted wirelessly from a communication device of the separately designed operating device to a communication device of the motor vehicle.

[0003] CN 1 07 392 336 A demonstrates an appointment-based, distributed charging system for electric vehicles in intelligent traffic. Charging stations send regular status updates to roadside units (CSSI update), which electric vehicles subscribe to (aggregated CSSI update). Based on this data, EVs make autonomous charging decisions and transmit reservations to roadside units (reservation aggregation). The charging station retrieves aggregated reservation data (aggregated charging reservation update). This reduces communication costs and optimizes charging processes.

[0004] DE 10 2015 203 149 A1 shows a system with a processor for detecting charging stations near a route, calculating charging costs including battery damage costs, displaying available stations with costs and estimated route time, receiving a selection and displaying a route with the selected charging stop. DESCRIPTION

[0005] The problem is solved by the subject matter according to claim 1. Further developments can be found in the subclaims.

[0006] The concepts described herein provide a method and associated system for selecting a charging station for a particular vehicle. The method includes determining, for the particular vehicle, a state of charge of an onboard DC power source arranged to supply electrical energy to a propulsion system for the particular vehicle. A route to a destination for the particular vehicle is determined, and the locations of multiple charging stations near the route for the particular vehicle are determined.Desired states and corresponding weighting factors for a plurality of user-selectable parameters are determined, and a sorting routine is executed to rank the plurality of charging stations near the travel route for the subject vehicle based on the desired states and the corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the vehicle's onboard DC power source. One of the plurality of charging stations is selected based on the ranking, and a charging reservation for the subject vehicle is scheduled using the selected charging station of the plurality of charging stations.

[0007] One aspect of the disclosure includes charging the on-board DC power source of the subject vehicle at the selected charging station from the plurality of charging stations based on the charging reservation.

[0008] Another aspect of the disclosure includes the plurality of user-selectable parameters including charging costs, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters includes determining a minimum charging cost, and wherein the weighting factor is inversely related to the charging cost.

[0009] Another aspect of the disclosure includes the plurality of user-selectable parameters including an expected wait time, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters includes determining a minimum expected wait time, and wherein the weighting factor is inversely related to the expected wait time.

[0010] Another aspect of the disclosure includes the plurality of user-selectable parameters including a deviation from a travel route, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters comprises determining a minimum deviation from the travel route, and wherein the weighting factor is inversely related to the deviation from the travel route.

[0011] Another aspect of the disclosure includes the plurality of user-selectable parameters including a point of interest, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters comprises determining a user preference associated with the point of interest, and wherein the weighting factor is directly related to the user preference associated with the point of interest.

[0012] Another aspect of the disclosure includes the plurality of user-selectable parameters including a point of interest, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters includes a set of charging points associated with one of the charging stations, and wherein the weighting factor is directly related to the set of charging points associated with one of the charging stations.

[0013] Another aspect of the disclosure includes the plurality of user-selectable parameters including a highway / urban route, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters includes a user preference associated with the highway / urban route, and wherein the weighting factor is directly related to the user preference associated with the highway / urban route.

[0014] Another aspect of the disclosure includes the plurality of user-selectable parameters, including customer ratings, and wherein determining desired states and corresponding weighting factors for the plurality of user-selectable parameters comprises determining a user preference associated with the customer ratings, and wherein the weighting factor is directly related to the customer ratings.

[0015] Another aspect of the disclosure includes determining a ranking for the plurality of charging stations based on the desired states and corresponding weighting factors for the plurality of user-selectable parameters, and the state of charge of the on-vehicle DC power source includes determining a ranking factor for each of the plurality of states of charge according to: Fi=(S*Wc*Wt*Wd*Wd*Wpoi*Wn*Wb*We*Wr) where: Fi represents a ranking factor for charging station i, where i represents one of the charging stations; and Wc represents a weighting factor related to the costs associated with charging station i, Wt represents a weighting factor associated with an expected waiting time associated with the charging station i, Wd represents a weighting factor associated with a deviation from the travel route associated with charging station i, The Wpoi represents a weighting factor associated with a point of interest connected to the charging station i, Wn represents a weighting factor associated with a number of charging points in the facility connected to charging station i, Wb represents a weighting factor associated with a provider preference associated with charging station i, We represent a weighting factor associated with a travel route connected to charging station i, and Wr represents a weighting factor associated with customer ratings related to charging station i.

[0016] The above summary is not intended to illustrate every possible embodiment or aspect of the present disclosure. Rather, the above summary is intended to illustrate some of the novel aspects and features disclosed herein. The above features and advantages, as well as other features and advantages of the present disclosure, will be readily apparent from the following detailed description of the representative embodiments and modes for carrying out the present disclosure when taken in conjunction with the accompanying figures and the appended claims. BRIEF DESCRIPTION OF THE CHARACTERS

[0017] One or more embodiments will now be described by way of example with reference to the accompanying figures, in which: Fig. 1 schematically illustrates the elements associated with selecting a desired charging station for a particular vehicle in accordance with the disclosure. Fig. 2 and Fig. 3 schematically illustrate a process for selecting and reserving a desired charging station and for performing a charging operation for a respective vehicle in accordance with the disclosure. Fig. 4 pictorially illustrates a road map depicting a desired travel route between a starting point and a destination and showing a plurality of possible charging stations according to the disclosure.

[0018] The accompanying figures are not necessarily to scale and may present a somewhat simplified representation of various preferred features of the present disclosure as disclosed herein, including, for example, specific dimensions, orientations, locations, and shapes. Details associated with such features will be determined in part by the particular intended application and use environment. DETAILED DESCRIPTION

[0019] The components of the disclosed embodiments described and illustrated herein can be arranged and configured in a variety of different configurations. Although numerous specific details are set forth in the following description to provide a thorough understanding of the embodiments disclosed herein, some embodiments may be practiced without some of these details. Moreover, for clarity, certain technical material understood in the related art has not been described in detail so as not to unnecessarily obscure the disclosure.

[0020] For convenience and clarity, directional terms such as top, bottom, left, right, up, down, under, over, back, and front may be used with reference to the figures.

[0021] As used herein, the term "system" refers to mechanical and electrical hardware, software, firmware, electronic control components, processing logic, and / or processor devices, individually or in combination, that provide the described functionality. This may include, without limitation, an application-specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or grouped) executing one or more software or firmware programs, a memory device containing software or firmware instructions, a combined logic circuit, and / or other components.

[0022] With reference to the figures, in which like reference numerals correspond to like or similar components in the different figures, Fig.1 schematically illustrates a vehicle 10, a charging station 50, an off-board server 30, and a cloud-based charging point database 40 in accordance with the embodiments disclosed herein, the interactions between which are managed by a charging station selection routine 200. Details related to one embodiment of the charging station selection routine 200 are described with reference to Fig.2. These elements may be associated with selecting a desired charging station 50 for the subject vehicle 10, scheduling a charging reservation for the subject vehicle 10 at the desired charging station 50, and executing a charging event for the subject vehicle 10 at the desired charging station 50. The method and apparatus for selecting, scheduling, and executing the charging event for the subject vehicle 10 at the desired charging station 50 advantageously utilizes the off-board server 30, the cloud-based charging point database 40, and the charging station selection routine 200.

[0023] After a period of energy depletion, the DC power source 14 may need to be recharged before further propulsion can be resumed. Such recharging may be accomplished by connecting the vehicle battery to an electrical power source, either directly or through one or more intermediate components, collectively referred to as a charging station 50. The charging station 50 may be a stationary device that may be located in a parking lot or other vehicle storage area, which may include one or more parking spaces, including, for example, a parking garage, a valet parking facility, a fleet vehicle storage area, etc. The desired charging station 50 may be a commercial or residential charging station capable of transferring electrical power from a stationary source to the subject vehicle 10.

[0024] The subject vehicle 10 is an electric vehicle, which may include any vehicle with a propulsion system 12 that uses electrical energy supplied from a DC power source 14 to generate traction power for vehicle propulsion. Some examples of electric vehicles include pure electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs), and extended-range electric vehicles (EREVs). These vehicles may include passenger cars, crossover vehicles, sport utility vehicles, recreational vehicles, trucks, buses, commercial vehicles, etc. The subject vehicle 10 may further include, but not be limited to, a mobile platform in the form of an industrial vehicle, an agricultural vehicle, an aircraft, a watercraft, a train, an off-highway vehicle, a personal mobility device, a robot, and the like, to fulfill the purposes of this disclosure.

[0025] The vehicle 10 comprises a controller 15, an on-board navigation system 16 including a GPS (Global Positioning System) sensor, a telematics system 17, and a human-machine interface (HMI) system 18. The navigation system 16 including the GPS sensor is capable of communicating with the cloud-based charging point database 40 and the off-board server 30 via the telematics system 17.

[0026] The HMI 18 provides human-machine interaction to control the navigation system 16 and other operations. These include selecting, scheduling, and executing a charging session for the respective vehicle 10 at a desired charging station 50.

[0027] The telematics system 17 comprises a wireless telematics communication system suitable for communication outside the vehicle, including communication with a communication network having wireless and wired communication capabilities. The telematics system 17 is suitable for communication outside the vehicle, including short-range vehicle-to-vehicle (V2V) communication and / or vehicle-to-vehicle (V2x) communication, which may also include communication with an infrastructure monitor, e.g., a traffic camera. Alternatively or additionally, the telematics system 17 has a wireless telematics communication system capable of conducting short-range wireless communication with a handheld device 20, e.g., a cellular phone, a satellite phone, or other telephony device.In one embodiment, the handheld device 20 is loaded with a software application including a wireless protocol for communicating with the telematics system 17, and the handheld device 20 performs the communication outside the vehicle, including communication with the off-board server 30.

[0028] The term "controller" or "controller" and related terms such as microcontroller, control unit, processor, and similar designations refer to one or various combinations of application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), electronic circuits, central processing units, e.g., microprocessors, and associated non-volatile memory components in the form of memory and storage devices (read-only, programmable read-only, random access, hard disk, etc.). The non-transitory memory component is capable of storing machine-readable instruction sets in the form of one or more software or firmware programs or routines, combinational logic circuits, input / output circuits and devices, signal conditioning and buffer circuits, and other components that can be accessed by one or more processors to provide a described functionality.Input / output circuitry and devices include analog-to-digital converters and related devices that monitor inputs from sensors, where these inputs are monitored at a preset sampling frequency or in response to a trigger event. Software, firmware, programs, instructions, control routines, code, algorithms, and similar terms refer to controller-executable instruction sets, including calibrations and lookup tables. Each controller executes control routine(s) to provide the desired functions. The routines may be executed at regular intervals, for example, every 100 microseconds during ongoing operation. Alternatively, routines may be executed in response to the occurrence of a triggering event.Communication between controllers, actuators, and / or sensors can be via a direct wired point-to-point connection, a networked communication bus connection, a wireless connection, or any other suitable communication link. Communication involves the exchange of data signals in a suitable form, including, for example, electrical signals via a conductive medium, an electromagnetic signal via air, optical signals via fiber optic cables, and the like. The data signals can be discrete, analog, or digitized analog signals representing inputs from sensors, actuator commands, and communication between controllers. The term “signal” refers to a physically perceptible indicator that conveys information and can be a suitable waveform (e.g., electrical, optical, magnetic, mechanical, or electromagnetic), such as:Direct current, alternating current, sine wave, triangular wave, square wave, oscillation, and the like, capable of moving through a medium. A parameter is defined as a measurable quantity representing a physical property of a device or other element that is detectable using one or more sensors and / or a physical model. A parameter can have a discrete value, e.g., either "1" or "0," or it can be continuously variable.

[0029] The term "signal" refers to a physically perceptible indicator that conveys information and may be any suitable waveform (e.g., electrical, optical, magnetic, mechanical, or electromagnetic), such as direct current, alternating current, sine wave, triangular wave, square wave, oscillation, and the like, capable of passing through a medium.

[0030] A parameter is defined as a measurable quantity that represents a physical property of a device or other element, detectable using one or more sensors and / or a physical model. A parameter can have a discrete value, e.g., either "1" or "0," or it can be continuously variable.

[0031] Fig. 2 and Fig. 3 schematically show an embodiment of the charging station selection routine 200 for selecting, scheduling and performing a charging process at a desired charging station for the vehicle described with reference to Fig.1. The charging station selection routine 200 provides a data-driven decision algorithm for evaluating potential charging stations based on user preferences, including distance and wait time, taking into account user preferences regarding wait time, travel distance, charging station type, cost factor, and characteristics of the location / area of the potential charging station. This allows users to select a desired charging point and charging station location based on the charging profile and travel time. This reduces the wait time or distance traveled to the desired charging station. Table 1 is provided as a key, in which the numerically labeled blocks and the corresponding functions according to the charging station selection routine 200 are shown as follows.The teachings may be described herein in terms of functional and / or logical block components and / or various processing steps. It should be noted that such block components may consist of hardware, software, and / or firmware components configured to perform the specified functions. Table 1 BLOCK BLOCK CONTENT 202 Route planning, request for cargo reservation 204 Communicate with the server 206 Query database 208 Route map available? 209 Advance to step 212 210 Calculate the distance(s) to potential charging station(s) 212 Determine parameters for potential charging station(s) based on proximity to the desired travel route 214 Determining the weight factors 216 Evaluate and rank the potential charging stations 218 Identify potential charging station(s) that match the search criteria 220 Display of potential charging station(s) that match the search criteria 222 Remove lowest rank condition 224 Are the constraints exhausted? 226 Display of the nearest potential charging stations 228 Request a reservation at the charging station 230 Show, suggest navigation 240 Reservation of cargo 242 Request a reservation 244 Notify charging station 246 Confirm reservation 248 Wait 250 Charging initiated? 252 Send cancellation request to other providers 254 Monitor SOC, charging interruptions 256 Inform operators about charging interruptions 260 Cancel reservation

[0032] The execution of the charging station selection routine 200 for the charging station can be carried out as follows. The steps of the charging station selection routine 200 can be carried out in any suitable order and are not limited to the steps described with reference to Fig. 2. As used herein, the term "1" means an affirmative answer or "YES" and the term "0" means a negative answer or "NO".

[0033] The charging station selection routine 200 is triggered when a vehicle operator executes a route planning event by selecting a desired destination and / or requesting a charging reservation via the HMI 18 or the handheld device 20 (202). This includes determining a state of charge (SOC) for the subject vehicle 10 for the DC power source 14 that supplies electrical power to the propulsion system 12, and a charging profile for the DC power source 14. The charging profile includes an expected charging time for charging the DC power source 14 based on a rating that includes a charging acceptance rate for the DC power source and the power output rate of the charging station, the available power (peak / off-peak power), the temperature, the type of charging point and connectors, the vehicle type, and the battery condition.

[0034] The SOC and the charge profile are used to determine an estimated remaining driving range for the affected vehicle 10.

[0035] The SOC and charging profile are also transmitted to the off-board server 30 (204), which queries the cloud-based charging station charging point database 40 (206) to identify the locations of a plurality of potential charging stations located near a desired travel route to the desired destination for the subject vehicle 10 and within the estimated remaining range of the subject vehicle 10, as well as related information. The related information for each of the potential charging stations includes electrical connector options and compatibility with the subject vehicle 10, charging system type, electricity costs, deviation from the desired travel route, charging station availability and wait time, and other factors.

[0036] If no route plan is available (208)(0), the routine (209) proceeds to step 212 as part of requesting a load reservation.

[0037] If the request includes a charging reservation request with a route plan (208)(1), the routine performs a series of steps to determine, quantify, and weight the user preferences to rank the potential charging stations that are close to the desired travel route to the desired destination for the subject vehicle 10 and within the estimated remaining travel range of the subject vehicle 10.

[0038] For each of the potential charging stations located near the desired travel route, the parameters are determined based on the proximity of the vehicle 10 in question to its current location (210). The parameters are determined based on the proximity to the desired travel route, i.e., the deviation from the desired travel route, and an associated travel time (212). These parameters include, as an example, a nearest point on the route to each charging point cp, which is expressed as follows: cp={(x1,y1),(x2,y2),(x3,y3),,(xn,yn)}

[0039] These parameters include a distance from the nearest point on the path d, which is expressed as follows: d={d1,d2,d3,…,dn}

[0040] These parameters include a nearest point of the vehicle in question c, which is expressed as follows: c={c1,c2,c3…,cn}

[0041] These parameters include an expected travel time taking into account weather and traffic delays t, which is expressed as follows: t={t1,t2,t3……tn}

[0042] Fig. 4 depicts a road map 400 depicting a desired travel route 405 between a starting point 402 and a destination 404. A plurality of potential charging stations are shown, labeled, among others, C1 411, C2 412, C3 413, and C4 414. Corresponding deviations (distances) from the travel route 405 associated with the potential charging stations are also depicted and labeled d1 421, corresponding to C1 411; d2 422, corresponding to C2 412; d3 423, corresponding to C3 413; and d4 424, corresponding to C4 424.

[0043] As in Fig. 2 and Fig.As shown in Figure 3, the weighting factors associated with each of the user preferences are determined, and the user preferences are incorporated into the evaluation using the weighting factors associated with each user preference (214). Examples of user preferences and weighting factors include weights for each of 1...n potential charging stations, e.g., C1 411, C2 412, C3 413, and C4 414.

[0044] The weighting factors include cost: Wc = {Wc1, Wc2...Wcn}, where weight is inversely related to cost; expected waiting time: Wt = {Wt1, Wt2...Wtn}, where weight is inversely related to expected waiting time; deviation from the travel route: Wd = {Wd1, Wd2...Wdn}, where weight is inversely related to distance or time from the travel route; point of interest (POI) match: Wpoi = {Wpoi1, Wpoi2....Wpoin}, where weight is directly related to POI match; number (quantity) of charging points in the facility: Wn = {Wn1, Wn2...Wnn}, where weight is directly related to the quantity of charging points; provider preference: Wb = {Wb1, Wb2....Wbn}, where weight is specific to provider preference. On the road (Interstate vs. City): We = {We1,We2...Wen}, where the weight is specific to the user preference for highway or city operation; and customer ratings: Wr = {Wr1, Wr2....Wrn}, where the weight is directly related to positive customer ratings, indirectly related to negative customer ratings, or a combination thereof.

[0045] Constraints can be applied to each of the potential charging stations as follows to evaluate and rank the potential charging stations (216), e.g., C1 411, C2 412, C3 413 and C4 414, which are relevant to Fig. 4, where the potential charging stations are evaluated and ranked based on the weight factors and restrictions.

[0046] Solution: S = Sort(d+c or t); or optimize for one of d, c, or t based on user preferences;

[0047] Apply restrictions: S < travel range left, d < maximum deviation from the route, cost c={min:max}, POI match=max, number of charging points >= user preferred, Provider = user input, On the go = user input, and t = estimated travel time.

[0048] For each of the potential charge states i, (i=1 to n) a rank factor Fi is determined as follows: Fi=(S*Wc*Wt*Wd*Wd*Wpoi*Wn*Wb*We*Wr) where: Fi represents a ranking factor for the charging station i, where i represents one of the charging stations; and Wc represents a weighting factor related to the costs associated with charging station i, Wt represents a weighting factor associated with an expected waiting time associated with the charging station i, Wd represents a weighting factor associated with a deviation from the travel route associated with charging station i, The Wpoi represents a weighting factor associated with a point of interest connected to the charging station i, Wn represents a weighting factor associated with a number of charging points in the facility connected to charging station i, Wb represents a weighting factor associated with a provider preference associated with charging station i, We represent a weighting factor associated with a travel route connected to charging station i, and Wr represents a weighting factor associated with customer ratings related to charging station i.

[0049] The rank factors Fi for the potential charge states i, (i=1 to n), are determined and sorted based on their respective magnitude and passed to step 218 for evaluation.

[0050] If one or more of the potential charging stations that meet the constraints based on the user preferences (218)(1) are identified (218), the potential charging stations that meet the constraints are displayed via the HMI 18, along with the associated rankings associated with the sorting by the ranking factor Fi, so that the vehicle operator can select one of the potential charging stations as the preferred charging station (220). The controller 15 communicates with the preferred charging station to request a charging reservation for the respective vehicle 10 (228), and the navigation system 16 determines a route to the preferred charging station.

[0051] The HMI 18 provides a visual display in the context of the navigation map to indicate one or more desired charging stations with their associated ranks and traffic and weather conditions, including road conditions related to congestion along the route (230).

[0052] If all potential charging stations are eliminated or do not meet the constraints based on user preferences (218)(0), the user preferences are evaluated to identify and eliminate the user preference or constraint with the lowest ranking from the evaluation (222), (224)(0), and the evaluation and ranking of the potential charging states is repeated (216) and re-evaluated to identify potential charging stations that meet the search criteria (218). This is an iterative process in which constraints are eliminated one by one based on their ranking.

[0053] If all constraints are removed (224)(1), the routine communicates via the HMI 18 that no desired locations have been identified. The routine also visually displays the locations of potential charging stations closest to the vehicle 10 in question, without taking into account any of the constraints (226) on the driver's selection of a desired charging station.

[0054] The controller 15 communicates with the desired charging station to request a charging reservation for the affected vehicle 10 (228), and the navigation system 16 determines a route to the desired charging station, which is displayed on the HMI 18. This also includes directing the operator of the affected vehicle 10 to the desired charging station.

[0055] With reference to Fig.3, the reservation request process (240) includes the operator requesting a reservation (242) with a notification to the desired charging station (244) and confirmation of the desired time from the desired charging station (246). In one embodiment, this may include the reservation request process (240) including the operator requesting multiple reservations at multiple requested times and locations, with notifications to the desired charging stations and confirmations of the requested times from the desired charging stations, as may occur on a trip requiring multiple charging events. If there is no confirmation from the desired charging station (246)(0), the operator is prompted to request a reservation at a different time or at a different desired charging state, and the reservation process begins again.If there is confirmation from the desired charging station (246)(1), the operator travels to the desired charging location and waits for the charging station to become available (248). If charging is not initiated after a specified period of time (250)(0), the operator is notified via their mobile device (258) with the option to continue charging at another location and cancel the reservation, or wait in a queue until one of the desired charging stations becomes available (260).

[0056] When initiating the charge collection (250)(1), a cancellation request is sent to other charging providers if the operator has duplicate reservations (252).

[0057] During the charging process, the battery's SOC is monitored along with the occurrence of charging interruptions (254), and the operator is kept informed via their mobile device (258). This may include, if locally available, notification of the source of a charging interruption, e.g., tampering by other users.

[0058] If a charging interruption occurs (256), the operator is notified via their mobile device (258), including any delay time. The operator has the option to continue charging at another location and cancel the reservation, or wait in a queue until one of the desired charging stations becomes available (260).

[0059] This allows user preferences, such as waiting time, shortest distance, charging point type, costs, and waiting time at the charging point location, to be used as input for a search ranking algorithm. Weights can be defined and normalized based on user preferences. Use the weighting factors to rank charging station locations. This also facilitates reservation booking at a preferred charging point or multiple charging points and can be configured to allow for multiple preferences for weekend / weekday / long-distance travel.

[0060] Embodiments consistent with the present disclosure may be embodied as an apparatus, method, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.), or an embodiment that combines software and hardware aspects and may be generally referred to herein as a "module" or "system." Furthermore, the present disclosure may take the form of a computer program product embodied in a tangible medium of expression embodying computer-usable program code within the medium.

[0061] Embodiments may also be implemented in cloud computing environments. In this description and the following claims, "cloud computing" can be defined as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released through virtualization with minimal management effort or service provider interaction, and then scaled accordingly. A cloud model can be composed of various characteristics (e.g., on-demand self-service, broad network access, resource pooling, rapid elasticity, metered service, etc.), service models (e.g., Software as a Service ("SaaS"), Platform as a Service ("PaaS"), Infrastructure as a Service ("IaaS")), and deployment models (e.g., private cloud, community cloud, public cloud, hybrid cloud, etc.).

[0062] The flowchart and block diagrams in the flowcharts illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code that includes one or more executable instructions for implementing the specified logical function(s). It should also be understood that each block of the block diagrams and / or flowchart representations and combinations of blocks in the block diagrams and / or flowchart representations may be implemented by dedicated-function hardware-based systems that perform the specified functions or acts, or combinations of dedicated-function hardware and computer instructions.These computer program instructions may also be stored on a computer-readable medium that can instruct a computer or other programmable data processing system to perform a particular function, such that the instructions stored on the computer-readable medium produce an article of manufacture including an instruction set that implements the function / effect specified in the flowchart and / or block diagram illustrations and / or block representations.

Claims

[1] A method for selecting a charging station (50) for a respective vehicle (10), the method comprising: Determining, for the vehicle (10) in question, a charge state of a vehicle-specific direct current source (14) which is configured to supply a drive system (12) for the vehicle (10) in question with electrical energy; Determining, for the vehicle in question (10), a travel route to a destination point; Determining desired states and corresponding weighting factors for a variety of user-selectable parameters; identifying locations of a plurality of charging stations located proximal to a travel route of the vehicle (10) in question; Determining a ranking factor for the plurality of charging stations based on the desired states and corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the vehicle's own DC power source (14); Selecting one of the plurality of charging stations based on the ranking factor; and scheduling a charging reservation for the vehicle (10) in question with the selected charging station from the plurality of charging stations, wherein determining a ranking for the plurality of charging stations based on the desired states and corresponding weighting factors for the plurality of user-selectable parameters and the state of charge of the vehicle's own DC power source (14) comprises determining a plurality of ranking factors for the plurality of charging stations and executing a sorting routine of the plurality of charging stations based on the plurality of ranking factors, where each of the plurality of ranking factors is determined according to: Fi=(S*Wc*Wt*Wd*Wd*Wpoi*Wn*Wb*We*Wr) where: Fi represents a ranking factor for the charging station i, where i represents one of the charging stations; and S = Sort(d+c or t); or optimize for one of d, c, or t based on user preferences; d < maximum deviation from the route, cost c = {min:max} and t = estimated travel time, Wc represents a weighting factor related to the cost associated with charging station i, Wt represents a weighting factor associated with an expected waiting time associated with the charging station i, Wd represents a weighting factor associated with a deviation from the travel route associated with charging station i, Wpoi represents a weighting factor associated with a point of interest connected to the charging station i, Wn represents a weighting factor associated with a number of charging points connected to the charging station i, Wb represents a weighting factor associated with a provider preference associated with charging station i, We represent a weighting factor associated with a travel route connected to charging station i, and Wr represents a weighting factor associated with customer ratings related to charging station i. [2] The method of claim 1, further comprising charging the on-board DC power source (14) of the subject vehicle (10) at the selected charging station from the plurality of charging stations based on the charging reservation. [3] The method of claim 1, wherein the plurality of user-selectable parameters includes a charging cost, and wherein determining the desired states and the corresponding weighting factors for the plurality of user-selectable parameters comprises determining a minimum charging cost, and wherein the corresponding weighting factor for the charging cost is inversely related to the charging cost. [4] The method of claim 1, wherein the plurality of user-selectable parameters comprises an expected wait time, and wherein determining the desired states and the corresponding weighting factors for the plurality of user-selectable parameters comprises determining a minimum expected wait time, and wherein the corresponding weighting factor for the wait time is inversely related to the expected wait time. [5] The method of claim 1, wherein the plurality of user-selectable parameters comprises a deviation from a travel route, and wherein determining the desired states and the corresponding weighting factors for the plurality of user-selectable parameters comprises determining a minimum deviation from the travel route, and wherein the corresponding weighting factor for the deviation from the travel route is inversely related to the deviation from the travel route. [6] The method of claim 1, wherein the plurality of user-selectable parameters comprises a point of interest, and wherein determining the desired states and the corresponding weighting factors for the plurality of user-selectable parameters comprises a user preference associated with the point of interest, and wherein the corresponding weighting factor for the user preference associated with the point of interest is directly related to the user preference associated with the point of interest. [7] The method of claim 1, wherein the plurality of user-selectable parameters comprises a point of interest, and wherein determining the desired states and the corresponding weighting factors for the plurality of user-selectable parameters comprises a set of charging points associated with one of the charging stations, and wherein the corresponding weighting factor for the user associated with the set of charging points associated with one of the charging stations is directly related to the set of charging points associated with one of the charging stations. [8] The method of claim 1, wherein the plurality of user-selectable parameters comprise a highway / urban travel route, and wherein determining the desired conditions and the corresponding weighting factors for the plurality of user-selectable parameters comprises a user preference associated with the highway / urban travel route, and wherein the corresponding weighting factor for the user preference associated with the highway / urban travel route is directly related to the user preference associated with the highway / urban travel route.

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