Method and system for charging an electric vehicle

Abstract

Methods for charging one or more electric vehicles are provided. The method comprises the following steps: receiving real-time available current information related to a main power supply through a main charging pile; receiving latest charging current information related to the main charging pile and one or more slave charging piles through the main charging pile, wherein the latest charging current information comprises charging modes and request charging current lists of the main charging pile and the one or more slave charging piles; through the main charging pile, processing the real-time available current information and the latest charging current information by applying a load balancing algorithm to generate a charging control signal; and applying a charging control signal to the master charging pile and the one or more slave charging piles to control charging of the one or more electric vehicles.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Patent Application Serial No. 63 / 591,450, filed on October 19, 2023, and entitled "Offline Auto LoadBalancing Algorithm for Multiple EV Charging Piles," the entire contents of which are hereby incorporated herein by reference. Technical Field

[0003] The present disclosure generally relates to electric vehicle (EV) charging. Background Art

[0004] The reference to any prior art in the specification does not constitute an acknowledgement or implication that the prior art forms part of the common general knowledge in any jurisdiction, nor does it imply that a person skilled in the art could reasonably expect that the prior art would be understood, regarded as relevant, and / or combined with other prior art.

[0005] In recent years, the number of EVs and plug-in hybrid electric vehicles (PHEVs) has increased rapidly because they can reduce pollution and carbon dioxide emissions compared to traditional gasoline vehicles. The growing popularity of EVs also reduces dependence on fossil fuels.

[0006] A series of international standards have been developed to manage EV charging. For example, the IEC 61851 series of standards developed by the International Electrotechnical Commission (IEC) is one of the earliest international standards for charging systems and provides an important reference for other countries to develop similar standards, such as the SAE J1772 standard in the United States and the GB / T standard in China. For these standards, the electric vehicle supply equipment (EVSE) has four modes, of which Mode 3 and Mode 4 are able to communicate with EVs to facilitate smart charging strategies. Mode 4 charging stations are high-power direct current (DC) stations designed for commercial use, requiring the support of high-capacity power grids and upgraded hardware facilities.

[0007] However, EV charging still faces significant challenges in various aspects. For example, the number of charging stations is far less than the number of EVs. This hinders the expectation that charging should be completed quickly, especially when time is limited. Therefore, this raises the question of how to better allocate power resources. For another example, a large number of EVs charging at high power at the same time will cause system overload and reduced load capacity. Summary of the invention

[0008] According to one or more embodiments, a method for charging one or more electric vehicles is provided. The method includes: receiving real-time available current information related to a main power source through a main charging pile; receiving the latest charging current information related to the main charging pile and one or more slave charging piles through the main charging pile, the latest charging current information including the charging mode and the requested charging current list of the main charging pile and the one or more slave charging piles; applying a load balancing algorithm through the main charging pile to process the real-time available current information and the latest charging current information to generate a charging control signal; and applying the charging control signal to the main charging pile and the one or more slave charging piles to control the charging of one or more electric vehicles.

[0009] According to one or more embodiments, a system for charging one or more electric vehicles is provided. The system includes a main charging pile and one or more slave charging piles communicating with the main charging pile. Each of the main charging pile and the one or more slave charging piles is configured to charge a corresponding electric vehicle in one or more electric vehicles. The main charging pile is configured to: receive real-time available current information related to the main power supply; receive the latest charging current information related to the main charging pile and one or more slave charging piles, the latest charging current information including the charging mode and the requested charging current list of the main charging pile and the one or more slave charging piles; generate a charging control signal by applying a load balancing algorithm to process the real-time available current information and the latest charging current information; and apply the charging control signal to the main charging pile and the one or more slave charging piles to control the charging of one or more electric vehicles.

[0010] Other example embodiments are discussed herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The detailed description is made with reference to the accompanying drawings. The drawings are for illustration purposes only and depict only example embodiments of the present disclosure. The drawings are provided to facilitate understanding of the present disclosure and should not be considered to limit the breadth, scope, or applicability of the present disclosure.

[0012] Figure 1 A system for charging one or more electric vehicles according to certain embodiments of the present disclosure is shown.

[0013] Figure 2 The hardware architecture implemented in a charging pile according to some embodiments of the present disclosure is shown.

[0014] Figure 3 The hardware implementation of the phase reconstruction module of the charging pile according to certain embodiments of the present disclosure is shown.

[0015] Figure 4 A method for charging one or more electric vehicles according to some embodiments of the present disclosure is shown.

[0016] Figure 5 Methods for charging one or more electric vehicles according to some other embodiments of the present disclosure are shown.

[0017] Figure 6 The actual charging current and the predicted required current of single-phase EV charging according to one embodiment of the present disclosure are shown, where C1, C2 and C3 represent the actual charging current.

[0018] Figure 7 The actual charging current and the predicted required current of single-phase EV charging according to another embodiment of the present disclosure are shown, where C1 , C2 , and C3 represent the actual charging current.

[0019] Figure 8 The actual charging current and the predicted required current of three-phase EV charging according to one embodiment of the present disclosure are shown, where C1, C2 and C3 represent the actual charging current.

[0020] Fig. 9 The actual charging current and the predicted required current of three-phase EV charging according to another embodiment of the present disclosure are shown, where C1 , C2 , and C3 represent the actual charging current.

[0021] Fig.10 The power data is shown when the main fuse is 1000A without using any charge management algorithm according to some embodiments of the present disclosure.

[0022] Fig.11 The power data of the main fuse of 1000A is shown using an averaging algorithm according to some embodiments of the present disclosure.

[0023] Fig.12 The power data of a main fuse of 1000A obtained by using a greedy and compression algorithm (GCA) according to certain embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0024] The present disclosure will now be described with reference to the following examples, which are to be considered in all respects as illustrative and non-restrictive.

[0025] Throughout the specification and claims, the words "include", "comprising", etc. should be interpreted in an inclusive sense, rather than an exclusive or exhaustive sense; that is, in the sense of "including but not limited to".

[0026] Furthermore, as used herein, unless otherwise indicated, the use of ordinal adjectives “first,” “second,” etc., to describe common objects merely indicates different instances of the similar objects referred to, and does not imply that the objects described must be arranged in a given order, whether temporal, spatial, ranked, or any other order.

[0027] Example embodiments are directed to methods and systems for EV charging that are improvements over prior art methods and / or systems.

[0028] Many existing EV charging technologies are unsatisfactory in one aspect or another. For example, the existence of single-phase EV charging and the non-ideal charging characteristics of three-phase EV charging lead to severe phase imbalance in the power grid. Various algorithms have been proposed to improve electric vehicle charging management. These algorithms include sequential quadratic optimization, dynamic programming, and heuristic methods. In practical applications, simple averaging algorithms have been used for load balancing. These existing methods are still unsatisfactory in solving the load imbalance problem.

[0029] For example, many existing methods require the use of solvers, especially those with non-convex objective functions or constraints. As a result, these methods require a lot of computing resources and time. The computing power of the microcontroller unit (MCU) of the charging pile is usually weak. Since charging has high real-time requirements, these existing methods may not be suitable for many applications, such as some non-networked practical scenarios. In addition, the simple averaging algorithm significantly reduces the utilization of electrical energy.

[0030] Example embodiments address one or more of these problems associated with existing methods and / or systems and provide technical solutions with improved performance.

[0031] One or more embodiments provide a method and / or system with one or more algorithms for achieving dynamic load balancing between multiple AC charging posts or charging stations. Compared with a simple averaging method or algorithm, experimental results show that the proposed algorithm improves the utilization of electric energy. Compared with existing algorithms that consume a large amount of computing resources, experimental results according to one or more embodiments show that the proposed algorithm can obtain a satisfactory solution in a shorter period of time.

[0032] One or more embodiments provide an effective and robust load balancing algorithm that models EV charging management under multiple charging piles as a three-machine scheduling problem and solves it using a novel greedy and compression algorithm (GCA). GCA prevents overload, improves energy utilization, and balances phases. According to one or more embodiments, the algorithm takes into account real-world constraints (for example, a three-phase EV can support both three-phase charging and single-phase charging, while a single-phase EV can control the charging phase).

[0033] In addition to online implementation, the proposed algorithm can also be deployed offline in charging stations with limited computing resources. Charging stations may be located in areas with poor network connectivity, such as underground or outdoor parking lots, which makes offline deployable algorithms more reliable. At the same time, the present disclosure proposes a corresponding feasible hardware framework and a basic charging pile hardware architecture. Experiments were conducted using generated datasets and real-world datasets under different capacity conditions, and the effectiveness of the proposed load balancing algorithm was demonstrated.

[0034] One or more embodiments innovatively model the multi-pile EV charging problem in a home three-phase circuit system as a multi-machine scheduling problem. The multi-machine scheduling problem assumes that there are n independent jobs that need to be processed by m machines, where job i requires time t i , and obtain the optimal job scheduling solution according to different requirements. According to one or more embodiments, the innovative solution is to regard the requested charging current of each EV for the corresponding charging pile as the job in the scheduling problem, and the residual current of each phase as the processing capacity of the machine. In order to solve this problem, the adopted GCA obtains a satisfactory solution in a short time. GCA can obtain a relatively optimal solution for multi-machine scheduling problems, and its solution process is relatively simple and fast. In some embodiments, compared with the solution obtained based on the optimization algorithm, the proposed algorithm significantly reduces the computational complexity and time spent.

[0035] In addition, the inventors have recognized that phase reconstruction can provide certain technical advantages for EV charging by improving electric vehicle charging management. In this regard, the inventors have proposed a phase reconstruction mechanism and its related algorithm for aligning the input phase of the power grid with different output phases. Experimental results according to one or more embodiments show that the proposed phase reconstruction mechanism improves energy efficiency and phase balance. In addition, the proposed phase reconstruction mechanism can achieve flexible management, such as providing charging for three-phase electric vehicles in a single-phase charging mode.

[0036] According to the IEC 61851 standard, the charging station can only communicate the phase-independent maximum charging current limit to the EV through the control pilot (CP). In other words, the IEC 61851 standard imposes a limit that the charging current of the EV cannot exceed the maximum current, denoted as I approved In some embodiments, I approved Also called the maximum approved charging current. The charge controller in an EV can adjust the current according to I approved The value of I in an AC charging station is usually approved falls within the range of approximately 6A to 32A. This range may vary in actual applications. Note that I approved Independent of the phase, this means that each phase of a three-phase charge must remain below this value.

[0037] With respect to the maximum current required by the IEC 61851 standard, existing methods generally set a fixed current value as the required current of the EV. These methods do not take into account the differences (such as actual status and demand) of various charging piles for EV charging, and therefore cannot efficiently and fairly distribute power between the charging piles and / or the EVs being charged.

[0038] In this regard, one or more embodiments introduce an EV charging required current prediction algorithm to forecast the required charging current. The forecasted or predicted required charging current is used as the requested charging current provided to the main charging pile for load balancing algorithm approval, thereby improving efficiency.

[0039] The inventors also note that existing methods generally ignore fairness or simply use average values ​​by assuming that all EVs and / or charging piles have the same charging requirements. The method and / or system according to one or more embodiments implements a required current prediction algorithm to achieve on-demand allocation and proportional fairness, thereby improving the efficiency of energy allocation and use.

[0040] One or more embodiments provide a feasible hardware framework including a charging pile hardware architecture. The method and / or system according to one or more embodiments can be implemented in relatively common embedded hardware (such as MCU, digital signal processor (DSP)) by implementing the proposed algorithm to achieve satisfactory results.

[0041] The inventors have conducted various experiments to investigate the performance and robustness of methods and systems implementing one or more of the algorithms presented herein. Randomly generated data and / or real world data were used for testing purposes. These results demonstrate superior performance in most, if not all, metrics compared to prior art non-coordinated charging and averaging algorithms lacking phase reconstruction functionality.

[0042] To ensure practical applicability, one or more embodiments adhere to the limitations set by the IEC 61851 series of standards and focus on the Mode 3 type AC EVSE specified in the IEC 61851 standard. It should be understood that these are only non-limiting examples to illustrate the inventive concepts and effectiveness of one or more aspects of the present disclosure.

[0043] Figure 1 A system for charging one or more EVs according to certain embodiments of the present disclosure is shown.

[0044] As shown, the system includes a main charging pile 110 and three slave charging piles 120, 130 and 140. The slave charging piles 120, 130 and 140 communicate with the main charging pile 110 for information exchange. For example, the slave charging pile can send its information to the main charging pile. The information may include, for example, a charging mode (e.g., single-phase or three-phase) and a requested charging current. The main charging pile may send a control signal (e.g., an approved charging current) to the slave charging pile to control the EV charging. Communication may be achieved through a wired or wireless connection. The number of slave charging piles may vary from one to more than three. The main charging pile and all slave charging piles are configured to charge EVs. When all charging piles are occupied, incoming EVs will queue up. Any slave charging pile may be appropriately modified to serve as a main charging pile. For example, the modification may include configuring the slave charging pile in a manner such that it includes and executes one or more load balancing algorithms and communicates with one or more other components described herein, thereby performing the functions of the main charging pile and achieving the results of the main charging pile according to one or more embodiments.

[0045] The main charging post 110 communicates with the power detection device 20. The power detection device 20 may include, for example, one or more current sensors. In the present embodiment, the power detection device 20 is connected to the main power source (e.g., the power grid) through the distribution box 10. The power detection device 20 detects the actual current of each of the three phases of the main power source. For each phase, the detected current is subtracted from the preset main fuse current to obtain the remaining available current. The remaining available current is provided to the main charging post 110, for example, through wireless communication.

[0046] Figure 2 2 shows a hardware architecture 220 implemented in a charging pile according to some embodiments of the present disclosure. The hardware architecture 220 can be implemented in one or more charging piles of a master charging pile and a slave charging pile, such as the above reference Figure 1 Those described.

[0047] As shown, the hardware architecture 220 includes a control module 221, a network communication module 222, a radio frequency (RF) communication module 223, a power monitoring module 224, a phase reconstruction module 225, and a charging support module 226. For example, the control module 221 includes one or more controllers for signal processing and generation. The network communication module 222 includes hardware and / or software components that enable one or more devices as described herein to communicate with one or more other devices through a certain protocol, including but not limited to Ethernet, Wi-Fi, Bluetooth, CAN bus, Zigbee, etc. The RF communication module 223 includes hardware and / or software that enables communication below 1 GHz, such as one or more of LoRa, Zigbee, Wi-sum, etc. The power monitoring module 224 includes components for measuring electrical variables, such as voltage, current, power, frequency, etc. The charging support module 226 includes one or more components that help manage and control the charging process of the EV by facilitating a safe and efficient charging process.

[0048] The phase reconstruction module 225 includes one or more hardware and / or software components that dynamically adjust the number of electrical phases used for EV charging based on factors such as available power, grid conditions, and the capabilities of the charging station. The phase reconstruction module 225 may include general-purpose computer hardware that is specifically programmed to implement certain algorithms to achieve one or more functions described herein. The inventors have recognized that phase reconstruction is particularly beneficial because it improves or optimizes charging efficiency and load balancing of the charging system according to one or more embodiments, where both single-phase charging and three-phase charging are available.

[0049] When the hardware architecture 220 is implemented in the main charging pile, one or more additional modules are also included, such as a module for executing one or more load balancing algorithms. These one or more additional modules can be implemented as part of certain modules as described above, such as the control module 221. It should be understood that the various modules shown in the hardware architecture 220 are for illustrative purposes only. The charging pile can be configured in different ways by modifying, removing or replacing one or more modules. For example, the RF communication module can be replaced with one or more other communication modules as long as the necessary communication between the devices in the charging system can be achieved. Although the phase reconstruction module brings certain technical advantages to the system and is preferred, it is not essential for the operation of one or more systems and / or methods according to one or more embodiments.

[0050] Figure 3 FIG. 3 shows the hardware design of the phase reconstruction module of the charging pile 306 according to some embodiments of the present disclosure. For example, the reconstruction module may be the phase reconstruction module of the charging pile 306 according to some embodiments of the present disclosure. Figure 2 The specific implementation of the phase reconstruction module 225. The charging pile 306 can be reference Figure 1 Any one of the main charging pile and the slave charging pile.

[0051] The phase reconstruction module is disposed in the charging pile 306 and includes a plurality of relays, denoted as R k , k∈1,...,5, that is, k is selected from the set consisting of 1, 2, 3, 4, 5. The number of relays can vary according to actual needs. The left side is the input side of the charging pile 306, which is the output of the distribution network 302. The right side is the output side of the charging pile 306, which is connected to the EV 304 during charging. For example, in single-phase charging mode, by default, phase A on the output side of the charging pile 306 is the EV charging input interface. Therefore, phase A, phase B or phase C on the input side of the charging pile 306 can be selected via a circuit to couple to phase A on the output side of the charging pile 306 to achieve phase configuration. The relay can be implemented as a switch controllable by a voltage level. In this embodiment, when R k = 0, the relay k is disconnected, the current is blocked and cannot flow; when R k =1, relay k is closed and current can flow. For example, in single-phase charging mode, when R1=1 and R2=R3=R4=R5=0, phase A on the input side of the charging pile 306 is coupled to phase A on the output side of the charging pile 306. This scenario corresponds to the standard single-phase charging mode. In the same single-phase charging scenario, by setting R2=1 and R1=R3=R4=R5=0, phase B on the input side of the charging pile 306 is coupled to phase A on the output side of the charging pile 306, thereby achieving phase reconstruction of single-phase charging using phase B of the grid. For three-phase charging, the relays can be set so that R1=R3=R5=1 and R2=R4=0. EVs capable of three-phase charging can also support single-phase charging. This can be achieved by configuring the relays in the same way as the single-phase charging setting.

[0052] It should be understood that the above reference Figure 3 The description is for illustration purposes only. For example, the input of the charging pile 306 is not necessarily connected to the output of the power distribution network. When the charging pile 306 is a slave charging pile, the input of the charging pile 306 can be connected to the output of the master charging pile. In addition, the relay can be configured as a more complex circuit rather than a simple switch.

[0053] Figure 4 A method for charging one or more EVs according to some embodiments of the present disclosure is shown. For example, the method may be implemented by a master charging pile and / or one or more slave charging piles, as described above with reference to one or more embodiments.

[0054] Block 402 represents receiving real-time available current information related to the main power source. For example, the real-time available current information includes the remaining available current received by the main charging pile from the power detection device.

[0055] Block 404 represents receiving the latest charging current information associated with the main charging pile and one or more slave charging piles. For example, the main charging pile may perform one or more actions and / or execute one or more algorithms therein to update and extract its information, including the charging mode and the requested charging current. The main charging pile may poll one or more slave charging piles to extract the charging mode and the requested charging current. The latest charging current information may include a list of charging modes and requested charging currents for the main charging pile and one or more slave charging piles. The charging mode may be single-phase charging or three-phase charging, which may depend on which mode is supported by the EV being charged. Each requested charging current is associated with a corresponding charging pile and may be determined based on various parameters, such as the actual charging current and the latest approved charging current, the total number of EVs being charged, etc. In some embodiments, the requested charging current may be generated by a current prediction algorithm to improve load balancing management. For example, each charging pile may measure the actual charging current used by the connected EV being charged, thereby obtaining the measured actual charging current. The charging pile may predict the requested charging current based on the measured actual charging current.

[0056] Block 406 represents generating a charging control signal by applying a load balancing algorithm to process the real-time available current information and the latest charging current information. The charging control signal can be generated by the master charging pile (e.g., by a control module therein) and used to control EV charging. For example, the master charging pile can generate an approved charging current so that each of the master charging pile and the slave charging pile knows what current should be applied to charge its connected EV. This can alleviate or reduce load imbalance and improve energy efficiency.

[0057] According to one or more embodiments, the request charging current list includes a first group of request charging currents for single-phase charging and a second group of request charging currents for three-phase charging. The first group of request charging currents is sorted in a non-decreasing manner to obtain the sorted first group of request charging currents. The sorted first group of request charging currents are sequentially allocated to the single charging phases with the smallest load for single-phase charging. This is an iterative process. Once the single charging phase with the smallest load is allocated, the second single charging phase with the smallest load will become the single charging phase with the smallest load and must be allocated. The iterative process continues until all single charging phases are allocated the sorted first group of request charging currents. Note that the single charging phase with the smallest load corresponds to the least busy charging piles for charging EVs in single-phase mode. The minimum load state may occur because the relevant charging pile is idle or the connected EV needs to charge slowly (for example, there may be no time urgency, and the EV stays there for overnight charging). Once all the sorted first groups of request charging currents are allocated, the second group of request charging currents are allocated to the three charging phases performing three-phase charging.

[0058] After all requested charging currents have been allocated, a new list of requested charging currents is obtained. The new list of requested charging currents may be part of a preliminary charging control signal for controlling EV charging. It is desirable that no charging phase is overloaded. Therefore, according to one or more embodiments, the preliminary charging control signal is further checked and adjusted before being used to control EV charging to ensure that no overloaded phase exists. For example, this may be accomplished by comparing the preliminary charging control signal to a maximum approved charging current. The maximum approved charging current may be the maximum current I specified in the IEC 61851 standard. approved . In some embodiments, the maximum approved charging current is 32A. Specifically, each requested charging current in the preliminary charging control signal is compared with the maximum approved charging current. If all requested charging currents are equal to or lower than the maximum approved charging current, it means that there is no overloaded phase. The preliminary charging control signal can be the final charging signal and is provided to the charging pile to control the EV charging. Otherwise, the requested charging current corresponding to the overloaded phase in the preliminary charging control signal is compressed with a corresponding compression factor to obtain a compressed charging control signal, wherein the compressed requested charging current is not greater than the maximum approved charging current. Doing so can avoid the problem of phase overload and achieve better EV charging performance.

[0059] Block 408 represents applying the charging control signal to the master charger and one or more slave chargers to control the charging of one or more electric vehicles. The master charger and the slave chargers determine the current used to charge the EV based on the charging control signal.

[0060] Figure 5A method for charging one or more EVs according to some other embodiments of the present disclosure is shown. For example, the method can be implemented by a master charging pile and / or one or more slave charging piles, as described above with reference to one or more embodiments. The method illustrates how to implement one or more proposed algorithms including a load balancing algorithm to improve EV charging.

[0061] Block 501 indicates the start of the process. Block 502 indicates that the current sensor detects the available current information of the main power distribution box and sends it to the main charging pile. The available current information includes, for example, the real-time current on the distribution box side obtained by reading the electric meter through the power detection chip. By presetting the main fuse size, the real-time available current and used current information for the three phases can be obtained.

[0062] Block 504 indicates that the central controller of the main charging pile polls all charging piles to obtain charging status and requirements, including various relevant information. Block 506 indicates the formation of a list of requested charging currents for single-phase charging and three-phase charging. For example, the main charging pile extracts the latest real-time actual three-phase charging current information from each of the main charging pile and the slave charging pile by polling. The main charging pile also obtains the charging mode (e.g., single-phase or three-phase) and the requested charging current. Assume that the number of main charging piles and one or more slave charging piles with a single-phase charging mode is N1, and the number of main charging piles and one or more slave charging piles with a three-phase charging mode is N2, and N=N1+N2. N1, N2 and N are integers, and N is greater than or equal to 1. N is also the total number of EVs being charged. A list of requested charging currents can be generated by placing the requested charging current for single-phase charging in the first N1 items, and placing the requested charging current for three-phase charging in the positions N1+1 to N1+N2. As well as the single-phase charging count N1, the three-phase charging count N2 and the total charging count N.

[0063] According to one or more embodiments, a list of requested charging currents may be generated at all charging posts by a current prediction algorithm. Each charging post implements a current prediction algorithm for predicting a corresponding requested charging current. This will be described below by way of example.

[0064] The i-th (i=1, ..., N) charging pile measures its actual charging current a in real time i , to predict the required charging current d for EV charging i The predicted required charging current will be used as the corresponding requested charging current r of the i-th charging pile. i , for load balancing.

[0065] Each charging pile maintains a charging information table to record the details of the current charging session. When a new charging session starts, the table will be cleared and updated with new data. The current prediction algorithm can be divided into two phases: initial phase and stable phase. The initial phase lasts from the start of EV charging until the predefined initialization time T init , and allows the EV time to stabilize in a constant current state. During this initial phase, the requested charging current is not based on the required charging current, but is set to the maximum preset charging current x of the charging station. max (This may be the maximum approved charging current, such as I approved , for example, 32A in some embodiments), and applied in a three-phase charging mode (the three-phase charging mode was initially selected because it was uncertain whether the EV supports single-phase charging or three-phase charging). At the end of the initial stage, the actual charging current a is measured. i If the measured current for any two phases is zero or close to zero, the EV is considered to be charged in a single phase; otherwise, it is identified as charged in a three-phase mode. In this way, the charging mode is determined and the charging information table of the charging pile is updated.

[0066] In the stable phase, according to the measured actual charging current a i Predict the required charging current d i Define or predetermine two thresholds δ inc (first threshold) and δ dec (Second threshold). Let c i is the latest approved charging current (i.e. the last approved charging current) of the main charging pile for the i-th charging pile. i -a i <δ inc ,but Among them, cnt inc Increments by 1. cnt inc Used as a continuously increasing counter and can be used when executing Figure 5 The method is initially set to zero. The symbol 'min' means to return the smaller of the two values ​​in the brackets. If c i -a i >δ dec , then d i =max(a i +1,6.0). The symbol 'max' means that the larger of the two values ​​in the brackets is returned. If neither condition is met, the required charging current remains d i unchanged, and cnt inc Reset to 0. After the prediction, the predicted required current d i As the requested charging current r for the i-th charging pile i , so that r i =di .

[0067] By using the current prediction algorithm, each charging pile device stores the current charging type or charging mode (single phase or three phase), real-time charging current information, and requested current information for the ongoing EV charging session. The central controller of the master charging pile can poll each charging pile (including the master charging pile) to extract such information. According to some embodiments, in order to prove the effectiveness of the current prediction algorithm, let T init = 120 seconds, δ inc = 0, and δ dec = 1.5. The current prediction algorithm is applied to real-world charging data for single-phase and three-phase charging. The results are as follows Figure 6 , Figure 7 , Figure 8 and Fig. 9 As shown in the following figures, C1, C2, and C3 represent the measured actual charging currents. The actual charging data set is obtained at 10-second intervals, i.e., recorded every 10 seconds. The figures also show the required current predicted using the proposed current prediction algorithm. Figure 6 and Figure 7 Corresponding to single-phase charging, C2 and C3 are both essentially zero. It can be seen that the current prediction algorithm can closely track the changes in charging data and modify δ inc and δ dec value to adjust the precision.

[0068] Reference again Figure 5 , block 508 represents data preprocessing. The data or information received from the current sensor and all the charging piles is processed at the master charging pile. The master charging pile considers various power-related information, such as household load, current used by the slave charging piles, etc. By adding the real-time available three-phase current information from the current sensor with the actual three-phase charging current information from all the slave charging piles, the available current information I of the jth phase (j∈1,2,3) excluding EV charging can be obtained. avail_j Therefore, I avail_j It can be expressed as "real-time available three-phase current information from the current sensor" plus "actual three-phase charging current information from all charging piles including the master charging pile and the slave charging pile". The following items can be input to the load balancing algorithm: The available current information I of the jth phase (j∈{1,2,3}) avail_j , the jth phase (j∈{1,2,3}) fixed current information I fix_j , request a list of charging currents Single-phase charging count N1, three-phase charging count N2. Fixed current information refers to the current associated with the system, such as the current required by household appliances. For some systems, it cannot be adjusted. Instead, it can be used as a known constraint for the algorithm.

[0069] Block 510 represents the execution of an online and / or offline algorithm. The output of the algorithm is a list of charging control signals, where the first N items represent load balancing control factors {λ1, ..., λ i ,…,λ N}, the last N items correspond to the approved charging currents {c1,…,c i ,…,c N}, there is a one-to-one correspondence between the two groups. The N items are the same as those in list request_charging_currents Therefore, after running the algorithm, the requested charging current information in the list can be obtained. chatging_controls ={λ1,…,λ N ,c1,...,c N} represents the charging control signal.

[0070] The following is an example of how to implement the load balancing algorithm. One of the tasks of the algorithm is to convert the three-phase available current I avail Evenly distribute to each charging pile to achieve load balancing control. This can be transformed into a parallel isomorphic three-machine scheduling problem with a maximum completion time constraint.

[0071] The parallel homogeneous multi-machine scheduling problem can be defined as follows. There are n tasks that need to be scheduled on m homogeneous machines. Each task j (where j = 1, ..., n) requires t j units of time to process. Each machine can only handle one task at a time. The goal is to assign n tasks to m homogeneous machines to minimize the completion time. In the context of load balancing, the three phases can be regarded as three homogeneous machines, where each task and its processing time can be compared to each single-phase charging pile and its requested current. Therefore, scheduling the requested charging current of single-phase charging among the three phases actually represents a three-machine scheduling challenge. As for the requested charging current of the three-phase charging piles, they can be directly distributed on all three phases at the same time. In addition, the constraint on the available current of the three phases is equivalent to the maximum completion time limit. To solve this problem, a compression algorithm is adopted.

[0072] In addition, the multi-machine scheduling problem is an NP-hard problem, but many heuristic algorithms have shown good performance in large-scale engineering problems, such as the shortest processing time (SPT) algorithm based on the greedy principle. One or more embodiments introduce a heuristic algorithm based on greed and compression, and the specific steps are as follows.

[0073] Greedy initialization allocation phase

[0074] The requested charging current (from list request_charging_currents The first N1 items, that is. ) are sorted in non-descending order. Then, each single-phase requested charging current is sequentially allocated to the single charging phase with the smallest load. That is, the sorted Assigned as The approved charging current for three-phase charging is then distributed to all three charging phases. Assigned as Thus, the preliminary results of load balancing control are obtained. charging_controls_preliminary ={λ1,…,λ N ,c1,...,c N}. The preliminary result represents a preliminary charging control signal. As for the load balancing control factors {λ1,…,λ i ,…,λ N}, for single-phase charging, if phase A is the phase with the smallest load, then λ i =1. Similarly, if it is phase B, then λ i =2, and if it is phase C, then λ i =3. If it is three-phase charging, then λ i =4. The preliminary charge control signal will be checked to ensure that no phase is overloaded. This can be done by setting each c i This is achieved by comparing with the maximum approved charging current (e.g. 32A). N The preliminary charge control signal is considered valid and applicable to the slave charger only when no element in} exceeds the maximum authorized charging current. Otherwise, the preliminary charge control signal must be further processed through the overload compression stage.

[0075] Overload compression stage

[0076] When there are one or more overloaded phases, a compression algorithm can be implemented. Let c i_min is the minimum approved charging current. The minimum approved charging current may be specified by the system or certain industry standards. In some embodiments, c i_min = 6.0 A. According to one or more embodiments, compression is not applied to the entire requested charging current in the preliminary charging control signal. Instead, it is applied to the redundant current z i =r i -c i_min The overload compression process unfolds as follows: a loop is started, wherein if the process has completed a preset number of complete iterations (e.g., three) or the result is valid, the loop is exited and the result is returned. First, the most severely overloaded phase is identified. most_overloading The term "most overloaded phase" refers to the electrical phase that experiences the highest degree of overload, meaning that it carries a current that exceeds its specified current limit by the largest margin. most_overloadingThe compression factor k is:

[0077]

[0078] For the requested charging current for single-phase charging, the compression value is determined as Then the compressed value Assigned as the new approved charging current, so that The compression calculation method for the requested charging current for three-phase charging is similar to that for single-phase charging, but the values ​​of the other two phases need to be updated with the same new approved charging current calculated. This is because the approved charging current for all three phases should be equal in three-phase charging. Therefore, if phase j most_overloading If there is a change, the other two phases also need to be updated accordingly. After compression, the cycle restarts. Finally, the updated or new charging control signal list is obtained. charging_controls ={θ1,…,λ N ,c1,...,c N The new charging control signal does not include any overload phase, and thus improved balanced load control can be achieved for EV charging.

[0079] Block 512 indicates that each charging post is notified of the corresponding load balancing factor and approved charging current. Block 514 indicates that each charging post applies charging control in the current EV charging session. Block 516 indicates the next time step and repeats the steps in the previous block, so that load control is a dynamic and real-time process. For example, the time step value can be set to 10 seconds. The time step value can be adjusted in actual application according to specific requirements to increase or decrease the time step duration.

[0080] As above reference Figure 4 and Figure 5 The method described is for illustrative purposes only. It is understood that one or more steps may be optionally configured and / or may be configured differently. It is understood by those skilled in the art that Figure 4 and Figure 5 The method steps can be combined in various ways. Figure 4 and Figure 5 The method steps may also be used to develop modified steps or new steps.

[0081] According to one or more embodiments, experiments are conducted to study the performance and robustness of the algorithm (e.g., GCA). The CGA is tested using randomly generated data and real-world data. The results are compared with those of the non-coordinated charging and average strategy algorithms based on the prior art. The analysis includes overload rate, approved charging EV rate, actual utilization, fairness, maximum phase difference, algorithm running time, and peak shaving effect.

[0082] Experimental setup

[0083] In one or more embodiments, the experiments are conducted on a 12th Generation Intel(R) Core(TM) i5-12400@2.50GHz, 8.00GB, Windows 10 system. All experimental codes are written in Python 3.10.11. The experiments require two types of data: power data from the distribution network and EV charging data. For experiments using randomly generated data, the EV charging data is generated based on basic EV charging characteristics, while the power data of the distribution network is adjusted within the range defined by the EV data and the capacity modification factor. Experiments using real-world data simulated EV charging in a residential area with 100 households. EV charging data were randomly selected from the EV-CPW dataset (reference: I. Ziyat, A. Gola, P. R. Palmer, S. Makonin, and F. Popowich, “Ev charging profiles and waveforms dataset (ev-cpw) and associated power quality analysis”, IEEE Access, 2023., the entire text of which is hereby incorporated herein) and the EV charging data of Nexblue Smart Charging. The power data of the distribution network were obtained from the three-phase household power data in northern Germany, reference: M. Schlemminger, T. Ohrdes, E. Schneider, and M. Knoop, “Dataset on electrical single-family house and heat pump load profiles in Germany”, Scientific data, vol.9, no.1, p.56, 2022, the entire text of which is hereby incorporated herein.

[0084] The average results of the experiments on one hundred sets of generated data are shown in Tables 1 and 2 below.

[0085] Table 1: Average performance on the generated dataset. Except for the approved charging EV rate (ACEVR) and actual utilization rate (AUR), where higher median values ​​indicate better performance, other indicators (overload rate (OLR), fairness (FAR), maximum phase current difference (MPCD)) tend to use lower values ​​close to zero. The three algorithms compared are no algorithm (NA) (i.e., no algorithm is used), average algorithm (AA), and greedy and compression algorithm (GCA). Bold marks indicate the best results for the two optimization objectives (AUR and FAR).

[0086] Model OLR ACEVR AUR FAR MPCD NA 0.9800 0.0200 0.0200 0.0000 29.1719 AA 0.0000 1.0000 0.7988 0.0252 1238.1231 CGA 0.0000 1.0000 0.9671 0.0034 19.7317

[0087] An overload occurs when the current usage exceeds the limit set by the main fuse. OLR measures the percentage of overload that occurs. ACEVR represents the proportion of EVs that are approved for charging to the total demand under the same capacity conditions. AUR reflects the efficiency of EV charging in utilizing grid power. Ideally, it should be the ratio of approved current to available current. However, the inventors have recognized that when the requested current is lower (for example, perhaps due to fewer charging vehicles), this ratio may be misleading and may not accurately reflect the effectiveness of the load balancing algorithm. Therefore, the inventors herein introduce the concept of AUR, as shown in the following formula:

[0088]

[0089] When the requested current is less than the available current, the AUR is the ratio of the approved current to the requested current, thus better representing the scheduling effectiveness of the algorithm. Note that the terms "approved_current" and "approved current" here have the same meaning as the term "approved charging current", and the terms "requested_current" and "requested current" have the same meaning as the term "requested charging current".

[0090] It is desirable to have the ratio of approved current to requested current for each EVSE to be as equal as possible. In one or more experiments described herein, the variance of this ratio was used as a standard fairness metric to measure FAR.

[0091] MPCD is the maximum phase current difference. Phase imbalance can cause various problems. For example, German regulations stipulate that the maximum phase current difference should be less than 20A.

[0092] Table 2: Average running time (ART) on the generated dataset. The two algorithms compared are the Greedy and Compressed Algorithm (GCA) and the NSGA-II algorithm (NSGA-II). The bold mark indicates the best result.

[0093] Model ART CGA 0.0005(s) NGCA-II 1.7450(s)

[0094] From these results, it can be seen that the proposed algorithm achieves significant improvements in various aspects, such as energy efficiency, overload prevention, phase balance, and fairness, compared with the no algorithm (without any charge management algorithm) and the commonly used average algorithm without phase configuration.

[0095] Furthermore, the proposed algorithm has significantly shorter running time (e.g., in this example, the average running time is only 0.0005 seconds) compared to resource-intensive algorithms, in particular a classic algorithm in multi-objective optimization: the non-dominated sorting genetic algorithm II (NSGA-II).

[0096] Experiments using real-world data

[0097] When the main fuse is set to 1000A, the full-day power consumption data under different algorithms in the real-world data experiment is as follows: Fig.10 , Fig.11 and Fig.12 shown.

[0098] It can be observed that the proposed method effectively reduces the peak current value and balances the current between phases when GCA is implemented. In contrast, the prior art uncoordinated charging and the averaging algorithm without phase reconstruction often lead to abnormally high peak current values ​​in phase A due to inefficient energy utilization, especially the uncoordinated charging leading to a prolonged overload occurrence time. In addition, significant three-phase imbalance is observed.

[0099] As used herein, the terms “charging post” and “charging station” may be used interchangeably.

[0100] It should also be understood that any features in the above embodiments of the present disclosure can be combined together, and do not have to be applied in isolation from each other. Those skilled in the art can easily make similar combinations of two or more features in the above embodiments or preferred forms of the present disclosure.

[0101] Technical and scientific terms used herein have the ordinary meanings commonly understood by those skilled in the art in relation to the exemplary embodiments, unless otherwise defined. It will be appreciated by those skilled in the art that many variations and / or modifications may be made to the above-described embodiments without departing from the broad general scope of the present disclosure. Therefore, the present embodiments are to be considered in all respects as illustrative and not restrictive.

Claims

1. A method for charging one or more electric vehicles, the method comprising: receiving real-time available current information related to the main power source through the main charging station; receiving, through the master charging pile, the latest charging current information related to the master charging pile and one or more slave charging piles, the latest charging current information including the charging modes and requested charging current lists of the master charging pile and the one or more slave charging piles; By means of the main charging pile, the real-time available current information and the latest charging current information are processed by applying a load balancing algorithm to generate a charging control signal; as well as The charging control signal is applied to the master charging pile and the one or more slave charging piles to control the charging of the one or more electric vehicles.

2. The method of claim 1, wherein the charging mode is selected from the group consisting of single-phase charging and three-phase charging.

3. The method according to claim 2, wherein the requested charging current list includes a first set of requested charging currents for single-phase charging and a second set of requested charging currents for three-phase charging, The generating of the charging control signal comprises obtaining a preliminary charging control signal by: sorting the first group of requested charging currents in a non-decreasing order to obtain a sorted first group of requested charging currents; sequentially allocating the sorted first group of requested charging currents to the single charging phase with the smallest load for the single-phase charging, and The second group of requested charging currents is distributed to three charging phases for the three-phase charging.

4. The method according to claim 3, wherein generating the charging control signal comprises: determining whether an overloaded phase exists by comparing the preliminary charge control signal with a maximum authorized charge current, and If no overloaded phase is identified, the preliminary charging control signal is assigned to the charging control signal.

5. The method according to claim 4, wherein generating the charging control signal comprises: If an overloaded phase is identified, then Calculate the compression factor; as well as The compression factor is applied to the overload phase to obtain a compression charging control signal for the overload phase.

6. The method according to claim 1, wherein receiving the latest charging current information comprises: The master charging pile and the one or more slave charging piles are polled by the master charging pile to extract the charging mode and the requested charging current list.

7. The method according to claim 1, further comprising: Measuring actual charging currents of the master charging pile and the one or more slave charging piles to obtain measured actual charging currents; as well as The requested charging current list is predicted based on the measured actual charging current.

8. The method according to claim 1, further comprising: The phases of the input and output for the master charger and each of the one or more slave chargers are reconfigured by relays.

9. The method according to claim 1, wherein the number of the master charging pile and the one or more slave charging piles is N, and N is an integer greater than 1. The method further comprises: At the i-th charging pile among the master charging pile and the one or more slave charging piles, i=1, ..., N: During the predefined initialization time period, the required charging current d of the i-th charging pile is set i , so that d i =x max , x max is the maximum approved charging current; At the end of the predefined initialization time period, the actual charging current a of the i-th charging pile is measured. i ; as well as According to the actual charging current a i , determine the charging mode of the i-th charging pile and update the required charging current d i .

10. The method according to claim 9, further comprising: If c i -a i <δ inc ,but, Update required charging current d i , so that c i is the latest approved charging current of the i-th charging pile, δ inc is the first threshold, cnt inc is a counter; and D i Assigned as the new approved charging current for the i-th charging post.

11. The method according to claim 9, further comprising: If c i -a i >δ dec ,but, d i =max(a i +1,x min ), c i is the latest approved charging current of the i-th charging pile, δ dec is the second threshold, x min is the minimum approved charging current; and D i Assigned as the new approved charging current for the i-th charging post.

12. The method according to claim 1, wherein receiving the latest charging current information comprises: polling the master charging pile and the one or more slave charging piles by the master charging pile to extract the latest charging current information from the charging information table, each charging information table being stored in a corresponding charging pile, Each charging information table includes a charging mode, an actual charging current and a required charging current for a corresponding charging pile, wherein the charging mode is a single-phase charging mode or a three-phase charging mode.

13. The method according to claim 1, further comprising: Based on the real-time available current information and the latest charging current information, the available current information I of the j-th phase (j∈1, 2, 3) is acquired. avail_j .

14. The method according to claim 13, wherein the number of the master charging pile and the one or more slave charging piles with a single-phase charging mode is N1, and the number of the master charging pile and the one or more slave charging piles with a three-phase charging mode is N2, and N=N1+N2, N1, N2 and N are integers, N is greater than or equal to one, and the requested charging current list is expressed as The charging control signal is represented as list charging_controls ={λ1,…,λ i ,…,λ N ,c1,…,c i ,…,c N },λ i represents the load balancing control factor of the i-th charging pile and is selected from any one of 1, 2, 3 and 4, c i represents the approved charging current of the i-th charging pile, The generating of the charging control signal comprises obtaining a preliminary charging control signal by: right Sort in non-descending order; After sorting As Assigned to the single charging phase with the smallest load for single-phase charging; and Will As Assigned to three charging phases for three-phase charging.

15. The method of claim 14, wherein generating the charging control signal comprises: determining whether there is an overloaded phase by comparing the preliminary charge control signal with a maximum authorized charging current; If any phase is overloaded, then: Calculate the redundant current z i =r i -c i_min , c i_min is the minimum approved charging current, z i =1,…,N; Repeat the following cycle until there are no overload phases: Identify the most severely overloaded phase most_overloading ; Calculation for phase most_overloading The compression factor k, in, The compression value is calculated as as well as Will Assign to Make in, 16. A system for charging one or more electric vehicles, the system comprising: Main charging station; as well as one or more slave charging piles communicating with the master charging pile, wherein each of the master charging pile and the one or more slave charging piles is configured to charge a corresponding electric vehicle among the one or more electric vehicles, The main charging pile is configured as: receiving real-time available current information associated with a main power source; Receiving the latest charging current information related to the master charging pile and the one or more slave charging piles, the latest charging current information including the charging modes and requested charging current lists of the master charging pile and the one or more slave charging piles; generating a charging control signal by processing the real-time available current information and the latest charging current information by applying a load balancing algorithm; as well as The charging control signal is applied to the master charging pile and the one or more slave charging piles to control the charging of the one or more electric vehicles. 17 . The system of claim 16 , wherein the master charger is configured to poll the master charger and the one or more slave chargers to extract the charging mode and the requested charging current list. 18 . The system according to claim 16 , wherein the master charging pile and each of the one or more slave charging piles comprises a phase reconstruction module for reconstructing the phase of the input and output for the corresponding charging pile through a relay.

19. The system according to claim 16, wherein the main charging pile is configured to obtain the j-th phase (j∈1,2,3) available current information I based on the real-time available current information and the latest charging current information avail_j , in, The number of the master charging pile and the one or more slave charging piles with a single-phase charging mode is N1, the number of the master charging pile and the one or more slave charging piles with a three-phase charging mode is N2, and N=N1+N2, N1, N2 and N are integers, N is greater than or equal to one, and the requested charging current list is expressed as: The charging control signal is represented as list charging_controls ={λ1,…,λ i ,…,λ N ,c1,…,c i ,…,c N },λ i represents the load balancing control factor of the i-th charging pile and is selected from the group consisting of 1, 2, 3 and 4, c i represents the approved charging current of the i-th charging pile, Wherein, the main charging pile is configured to obtain a preliminary charging control signal in the following manner: In non-descending order Sort by After sorting As Assigned to the single charging phase with the smallest load for single-phase charging; and Will As Assigned to three charging phases for three-phase charging, The main charging pile is further configured as: determining whether an overloaded phase exists by comparing the preliminary charge control signal with a maximum authorized charge current; If any overloaded phase exists, then: Calculate the redundant current z i =r i -c i_min , c i_min is the minimum approved charging current, z i =1,…,N; Repeat the following cycle until there are no overload phases: Identify the most severely overloaded phase most_overloading ; Calculation phase most_overloading The compression factor k, in, The compression value is calculated as as well as Will Assign to Make in 20. The system of claim 16, further comprising a power detection device for measuring real-time available current information associated with the main power source.

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