Self-adaptive charging control method of electric vehicle and electric vehicle

Abstract

The invention provides a self-adaptive charging control method of an electric vehicle and the electric vehicle, the method is applied to the electric vehicle which performs data interaction with power supply equipment through a PLC signal coupled to a charging control guiding signal, and the method comprises the following steps: when connection with the power supply equipment is confirmed, after communication connection is established according to a communication address of the power supply equipment, the PLC signal is sent to the PLC signal; executing a service information interaction process; executing a charging parameter acquisition process, acquiring an equipment charging parameter, a target charging mode and vehicle body charging information, and generating an optimal charging parameter based on a corresponding preset charging parameter optimization model according to the equipment charging parameter, the target charging mode and the vehicle body charging information; and after the optimal charging parameters are sent to the power supply equipment, a charging task is executed according to a target charging mode and the optimal charging parameters. Intelligent management of the alternating current charging process can be achieved, and the charging efficiency, the charging safety and the charging control flexibility of the vehicle are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging control, and in particular to an adaptive charging control method for an electric vehicle and the electric vehicle. Background Art

[0002] As a clean and efficient means of transportation, electric vehicles play an important role in reducing air pollution and greenhouse gas emissions. However, the widespread use and popularization of electric vehicles still faces many challenges, charging being one of them. Based on this, the research and development of efficient and intelligent electric vehicle charging control methods has important practical significance and application value.

[0003] The existing charging design of electric vehicles will establish a communication connection and exchange information based on the CAN communication mode during DC charging, and the charging information will be updated in real time according to the interactive data between the two parties during the charging process, so as to perform intelligent charging control. In the AC charging scenario, the charging current at the power supply device end is only obtained through the PWM signal duty cycle, and the charging demand cannot be updated and controlled in time during the entire charging process, that is, it is difficult to achieve intelligent adaptive charging control. For example, during the AC charging process, the charging control system cannot dynamically adjust the charging parameters according to the actual state of the vehicle battery, the charging power at the power supply device end, the charging cost and other factors, resulting in low charging efficiency, and even the possibility of charging failures due to inappropriate charging parameters and undiscovered accidents. Therefore, it is urgent to provide an intelligent management method that can realize adaptive regulation of charging parameters during AC charging to improve the charging efficiency and charging safety of electric vehicles. Summary of the invention

[0004] The purpose of the present invention is to provide an adaptive charging control method for electric vehicles, wherein the electric vehicle interacts with a power supply device for charging services, charging parameters and other data via a PLC signal coupled to a charging control guide signal, and the electric vehicle calculates and generates optimal charging parameters based on the acquired charging parameters in combination with charging strategy optimization targets under different charging modes and feeds them back to the power supply device for use, and can perceive changes in the charging environment at the power supply device end and changes in the electric vehicle demand in real time during the AC charging process, adaptively adjust the charging parameters at the electric vehicle end, realize intelligent management of the electric vehicle AC charging process, and effectively improve the charging efficiency and charging safety of the electric vehicle.

[0005] In order to achieve the above objectives, it is necessary to provide an adaptive charging control method for an electric vehicle and an electric vehicle in response to the above technical problems.

[0006] In a first aspect, an embodiment of the present invention provides an adaptive charging control method for an electric vehicle, which is applied to an electric vehicle that performs data interaction with a power supply device via a PLC signal coupled to a charging control pilot signal; the method comprises the following steps:

[0007] S10, after confirming the connection with the power supply device, obtaining the communication address of the power supply device, establishing a communication connection according to the communication address, and executing a service information interaction process; the service information interaction process is used to perform various service information interactions with the power supply device, including application protocol request, session establishment, service acquisition and identification verification;

[0008] S20, executing a charging parameter acquisition process to acquire device charging parameters, a target charging mode, and vehicle body charging information, and generating optimal charging parameters based on a corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode, and the vehicle body charging information; the preset charging parameter optimization model is an expected charging current optimization model constructed based on charging optimization targets of different target charging modes and taking the device charging parameters and the vehicle body charging information as optimization conditions;

[0009] S30: After sending the optimal charging parameters to the power supply device, execute the charging task according to the target charging mode and the optimal charging parameters.

[0010] Furthermore, in step S20, a charging parameter acquisition process is executed, and the step of acquiring a target charging mode includes:

[0011] S201, sending a charging mode request to a corresponding vehicle-associated mobile terminal and starting a corresponding request response timer;

[0012] S202: when the request response timer has not timed out and a corresponding charging mode request response is received, setting the target charging mode according to the charging mode request response;

[0013] S203: When the request response timer times out and the charging mode request response is not received, setting the target charging mode to a reserved charging mode.

[0014] Further, in step S20, the target charging mode includes an immediate charging mode and a scheduled charging mode. When the target charging mode is the immediate charging mode, the step of generating optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes:

[0015] S204, generating the optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information; the immediate charging parameter optimization model is constructed with minimizing the charging time as the optimization goal; the objective function of the immediate charging parameter optimization model is expressed as:

[0016]

[0017] In the formula, T represents the charging time; Soc s and Soc e They represent the current battery state of charge and the target battery state of charge respectively; E represents the battery capacity; η represents the charging efficiency; U and I represent the charging voltage and charging current respectively.

[0018] Furthermore, the device charging parameters include a maximum charging current, a minimum charging current, a maximum charging voltage, and a minimum charging voltage; the vehicle body charging information includes a battery capacity, an allowable charging voltage, a current battery state of charge, a target battery state of charge, a cable rated current, and a maximum required battery current;

[0019] In step S204, the step of generating optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information includes:

[0020] S2041. Determine a charging power constraint according to the device charging parameter;

[0021] S2042, according to the battery capacity, the allowable charging voltage, the current battery state of charge and the target battery state of charge in the vehicle body charging information, solving the immediate charging parameter optimization model with the charging power constraint as a constraint condition to obtain the expected charging current;

[0022] S2043. Obtain the expected charging current and the minimum current value of the cable rated current and the battery maximum required current in the vehicle body charging information, and generate the optimal charging parameter according to the minimum current value and the allowable charging voltage.

[0023] Further, in step S20, the target charging mode includes an immediate charging mode and a scheduled charging mode. When the target charging mode is the scheduled charging mode, the step of generating optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes:

[0024] S205. Generate the optimal charging parameters based on the corresponding scheduled charging parameter optimization model according to the device charging parameters and the vehicle body charging information; the scheduled charging parameter optimization model includes a scheduled time period optimization model with minimizing user charging costs as the optimization goal, and a time period charging parameter optimization model with minimizing grid load fluctuations as the optimization goal.

[0025] Furthermore, in step S205, the objective function of the reservation time period optimization model is expressed as:

[0026]

[0027] Among them, F1 represents the user's charging cost; B t P represents the charging price per unit of electricity at time t; t represents the charging power at time t; t1 and t2 represent the charging start time and charging end time respectively.

[0028] Further, in step S205, the objective function of the time period charging parameter optimization model is expressed as:

[0029]

[0030] In the formula,

[0031]

[0032]

[0033] Among them, F2 represents the grid load fluctuation; Indicates the target charging period; P s (t) represents the equivalent load power at time t; P avg Indicates average load power; P load (t) and P EV (t) represent the basic load power when no electric vehicle is connected to the grid at time t and the load power when an electric vehicle is in charging state; X c (t) and P c represents the charging status and charging power of electric vehicle c at time t; N represents the total number of electric vehicles connected to the power grid in the power grid area at time t.

[0034] Furthermore, the equipment charging parameters include the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the power grid area electricity price list, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle; the vehicle body charging information includes the battery capacity, the allowable charging voltage, the current battery state of charge, the target battery state of charge, the cable rated current and the maximum required battery current;

[0035] In step S205, the step of generating optimal charging parameters based on the corresponding scheduled charging parameter optimization model according to the device charging parameters and the vehicle body charging information includes:

[0036] S2051, calculating an estimated charging time according to the battery capacity, current battery state of charge and target battery state of charge in the vehicle body charging information, and obtaining a minimum value between the estimated charging time and the charging time set by the user as the scheduled charging time;

[0037] S2052, solving the reservation period optimization model according to the scheduled charging duration, the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage and the power grid area electricity price table in the device charging parameters, and obtaining at least one optimal scheduled charging period;

[0038] S2053, sending all optimal scheduled charging time periods to the corresponding vehicle-associated mobile terminal to obtain the user's desired charging time period;

[0039] S2054, solving the charging parameter optimization model for the time period according to the user's expected charging time period, the allowed charging voltage in the vehicle body charging information, and the device charging parameters including the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle, to obtain the scheduled expected charging current;

[0040] S2055. Obtain the minimum current value among the expected charging current and the cable rated current and the maximum battery demand current in the vehicle body charging information, and generate the optimal charging parameters according to the minimum current value, the allowed charging voltage and the user's expected charging period.

[0041] Furthermore, in step S30, the method further includes:

[0042] S301. During the charging process, the latest charging parameters are periodically obtained from the power supply device through the PLC signal, and real-time optimal charging parameters are generated based on the latest charging parameters and the latest vehicle body charging information based on the corresponding preset charging parameter optimization model, and the real-time optimal charging parameters are sent to the power supply device to adjust the charging power in real time.

[0043] In a second aspect, an embodiment of the present invention provides an electric vehicle, which interacts with a power supply device via a PLC signal coupled to a charging control guidance signal, and includes an adaptive charging control device; the adaptive charging control device implements the steps of the above method when performing charging control.

[0044] The present invention provides an adaptive charging control method for an electric vehicle and an electric vehicle. The method enables the electric vehicle to interact with a power supply device through a PLC signal coupled to a charging control guide signal. After confirming the connection with the power supply device, the communication address of the power supply device is obtained. After establishing a communication connection according to the communication address, the service information interaction process and the charging parameter acquisition process including application protocol request, session establishment, service acquisition and identification verification are sequentially executed, and in response to a charging parameter acquisition response signal, the device charging parameters, target charging mode and vehicle body charging information are obtained. According to the device charging parameters, target charging mode and vehicle body charging information, the optimal charging parameters are generated based on a preset charging parameter optimization model constructed based on the charging optimization targets of different target charging modes and the corresponding device charging parameters and vehicle body charging information are used as optimization conditions. After the optimal charging parameters are sent to the power supply device, a technical solution for executing the charging task according to the target charging mode and the optimal charging parameters is implemented. Compared with the existing technology, the adaptive charging control method of electric vehicles can perceive the changes in the charging environment of the power supply equipment and the electric vehicle needs in real time during the AC charging process, adaptively adjust the charging parameters of the electric vehicle, and realize the intelligent management of the AC charging process of the electric vehicle. It can not only effectively improve the charging efficiency and charging safety of the electric vehicle, but also realize personalized management of charging needs and improve the flexibility of charging control. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of an adaptive charging control method for an electric vehicle in an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of an AC charging control design in which PLC modules are respectively installed at both ends of a power supply device and an electric vehicle in an embodiment of the present invention;

[0047] Figure 3 It is a detailed AC charging control design schematic diagram in which PLC modules are respectively installed at both ends of the power supply equipment and the electric vehicle in an embodiment of the present invention;

[0048] Figure 4 It is a schematic diagram of an architecture based on PLC signal communication in an embodiment of the present invention;

[0049] Figure 5 is a schematic diagram of a control and guidance circuit for AC charging in an embodiment of the present invention;

[0050] Figure 6 In the embodiment of the present invention, the power supply device is based on Figure 5 The state transition diagram of the control guidance circuit shown in FIG.

[0051] Figure 7 It is a schematic diagram of the communication interaction process of the adaptive control of AC charging in an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical scheme and beneficial effects of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Obviously, the embodiments described below are part of the embodiments of the present invention and are only used to illustrate the present invention, but are not used to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] The adaptive charging control method for electric vehicles provided by the present invention can be understood as an adaptive charging parameter control method in which an electric vehicle interacts with a power supply device through a PLC signal coupled to a charging control guide signal to perform charging services and charging parameter data, and the electric vehicle generates optimal charging parameters based on the acquired charging parameters combined with the charging strategy optimization target under different charging modes and feeds them back to the power supply device for use. The following embodiments will explain the adaptive charging control method for electric vehicles of the present invention in detail.

[0054] In one embodiment, Figure 1 As shown, an adaptive charging control method for electric vehicles is provided, which is applied to electric vehicles that interact with power supply equipment through PLC signals coupled to charging control guidance signals; wherein the power supply equipment (Electric Vehicle Supply Equipment, EVSE) can be understood as a device that is connected to an electric vehicle (Electric Vehicle, EV) through a charging gun and supplies power to the electric vehicle, including a charging pile or other supporting charging equipment. In practical applications, Figure 2 In the AC charging control design shown in the figure, a PLC module capable of sending a PLC signal coupled to a charging control pilot signal (CP signal) is installed at both ends of the power supply device and the electric vehicle, so that the electric vehicle and the power supply device can exchange data based on the PLC signal, thereby realizing intelligent control of AC charging. The specific design for coupling the PLC signal with the CP signal is as follows: Figure 3 As shown: In power supply equipment and electric vehicles, connect C between CP line and ground terminal PLC Capacitor and C PLC The PLC module with capacitors in series has a PLC The common end of the capacitor is connected to the inductor L, and the resistor R is connected in parallel at both ends of the inductor L. DampAt the same time, connect the other end of the inductor L to the first detection point; in this design, the inductor L and the resistor R Damp The low-pass filter can be used to prevent the high-frequency signal of the PLC module from interfering with the state of the CP line and the original PWM signal, and through C PLC The capacitor isolates the PWM signal from entering the PLC module to achieve safe interaction of the PLC signal coupling with the charging control pilot signal (CP signal). Figure 2 and Figure 3 The design of other parts shown except for adding PLC module communication can be obtained by referring to the existing AC charging control design. The physical meanings corresponding to the letter symbols can all be explained in the prior art and will not be repeated here.

[0055] It should be noted that the structure of PLC signal communication is as follows Figure 3 The figure shows 7 layers, including physical layer, data link layer, network layer, transport layer, session layer, presentation layer and application layer. Among them, the physical layer is the charging cable, the data link layer is the PLC carrier, the network layer adopts the IPV6 version, including IP, IMCP and SLAAC (Stateless Address Autoconfiguration) mechanism; the transport layer adopts TCP / IP, UDP or TLS (Transport Layer Security) communication, and the session layer adopts GTPv2 (GPRS Tunneling Protocol version 2); the presentation layer adopts the EXI (Extensible Markup Language) encoding format, and the application layer is implemented based on the SDP (Session Description Protocol) protocol. In practical applications, the method of generating PLC signals based on the PLC signal communication structure through the PCL module can be implemented by referring to the relevant existing technology, which will not be described in detail here.

[0056] based on Figure 3 The PLC signal communication design between the electric vehicle and the power supply device shown in the figure, the adaptive charging control method during the AC charging process of the electric vehicle provided by the present invention comprises the following steps:

[0057] S10, after confirming the connection with the power supply device, obtaining the communication address of the power supply device, establishing a communication connection according to the communication address, and executing the service information interaction process; wherein, the process of confirming the connection between the electric vehicle and the power supply device can be understood as the electric vehicle being awakened by the charging gun being inserted, and the charging control module in the vehicle controller of the electric vehicle is based on Figure 5The control guidance circuit shown in the figure guides the electric vehicle to the process of being ready to receive energy. After the gun is plugged in, R3 at the electric vehicle end divides the voltage, and the voltage at the detection point 2 at the electric vehicle end changes from 0V to 9V. At the same time, the CC signal at the detection point 3 is an effective value (effective value as shown in Table 1), and the voltage at the monitoring point 1 at the power supply device end changes from 12V to 9V, then the state changes from Figure 6 The State1 shown changes to State2, that is, the electric vehicle and the power supply device are connected, the CP voltage at the electric vehicle end changes from 0V to 9V, the resistance value of CC is an effective value, and the CP voltage at the power supply device end changes from 12V to 9V.

[0058] Table 1 Effective CC resistance when electric vehicle and power supply equipment are connected

[0059]

[0060] In practical applications, Figure 6 The state transition process implemented by the power supply device based on the control guidance circuit is as follows:

[0061] State 1: The charging gun is not connected to the electric vehicle, and the PWM switch on the power supply device is not closed;

[0062] State 1': The charging gun is not connected to the electric vehicle, and the PWM switch on the power supply device is closed;

[0063] State 2: The charging gun is connected to the electric vehicle, and the PWM switch on the power supply device is not closed; State 2': The charging gun is connected to the electric vehicle, and the PWM switch on the power supply device is closed;

[0064] State 3: The electric vehicle is ready to receive energy, and the PWM switch on the power supply device is not closed; State 3': The electric vehicle is ready to receive energy, and the PWM switch on the power supply device is closed.

[0065] like Figure 7As shown, after the electric vehicle and the power supply equipment both confirm the connection, the switch S1 of the power supply equipment is switched from 12V to 12V PWM, and the state of the power supply equipment is converted from State2 to State 2'; after the electric vehicle obtains the IP address and port number of the power supply equipment (which can be achieved through SDP technology), it quickly establishes a communication connection, and obtains the application protocol (optional protocol, such as 15118, 70121, etc.) that the power supply equipment can provide through the supportAppProtocolRes signal, the protocol version number and the corresponding ID number in the power supply equipment, as well as the priority of each protocol when multiple protocols are met at the same time; the electric vehicle selects its own matching protocol service based on the information obtained, and then obtains the charging method service that the power supply equipment can provide based on the ServiceDiscoveryRes signal that interacts with the PLC communication of the power supply equipment, and then implements information interaction verification and payment method selection based on further PLC communication. It should be noted that the signal description involved in the communication process between the electric vehicle and the power supply equipment during AC charging is shown in Table 2, and for the convenience of description, the application protocol request, session establishment, service acquisition and identification verification processes are summarized as service information interaction processes (used to interact with the power supply equipment for various service information). The specific implementation of each process interaction can refer to the relevant existing technology implementation, which will not be described in detail here.

[0066] Table 2 Communication process interaction signals between electric vehicles and power supply equipment

[0067]

[0068]

[0069] S20, execute the charging parameter acquisition process, obtain the device charging parameters, the target charging mode and the vehicle body charging information, and generate the optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information; wherein, the charging parameter acquisition process can be understood as the process of the electric vehicle obtaining the charging parameters from the power supply device for the first time based on the interaction between the charging parameter acquisition request ChargeParamterDiscoveryReq signal and the charging parameter acquisition response ChargeParamterDiscoveryRes signal in Table 2 after completing the service information interaction process. The specific implementation can refer to the relevant existing technology and will not be described in detail here. It should be noted that the charging parameters of the power supply device side replied by the power supply device side include the power grid area electricity price table, the maximum charging current, minimum charging current, maximum charging voltage, minimum charging voltage and some other charging-related parameters that the current power grid can provide, which can be set according to the actual application scenario.

[0070] When the electric vehicle receives the charging parameter acquisition response signal and obtains the transmitted device charging parameters as described above by parsing the signal, it can send a charging mode request to the mobile terminal (such as the mobile phone) bound to the electric vehicle to obtain the target charging mode (immediate charging mode or scheduled charging mode) selected by the user according to his current needs. The vehicle body charging information can be understood as the battery charging constraint information of the electric vehicle itself, such as battery capacity, allowable charging voltage, current battery state of charge, target battery state of charge, cable rated current and maximum battery demand current, etc., which can be preferably set according to actual application needs.

[0071] Specifically, in step S20, the charging parameter acquisition process is executed, and the step of acquiring the target charging mode includes:

[0072] S201. Send a charging mode request to the corresponding vehicle-associated mobile terminal and start a corresponding request response timer; wherein, the timeout duration of the request response timer can be set according to actual application requirements and is not limited here.

[0073] S202. When the request response timer has not timed out and a corresponding charging mode request response is received, the target charging mode is set according to the charging mode request response; that is, the immediate charging mode or the reserved charging mode returned by the mobile terminal obtained before the request response timer has not timed out is directly used as the obtained target charging mode.

[0074] S203. When the request response timer times out and the charging mode request response is not received, the target charging mode is set to the reserved charging mode; that is, if the mobile terminal does not return to the target charging mode within a specified time, the target charging mode is directly set to the reserved charging mode.

[0075] It should be noted that after the target charging mode is obtained through the above method steps, it needs to be stored so that when the scheduled charging vehicle is woken up again, it can directly read that the current charging mode is the scheduled charging mode for charging parameter optimization.

[0076] The preset charging parameter optimization model in this embodiment can be understood as an expected charging current optimization model constructed based on the preset charging optimization targets under different target charging modes, with the device charging parameters and the vehicle body charging information as optimization conditions; that is, the specific preset charging parameter optimization model varies depending on the target charging mode, and the corresponding optimization targets are also different; the following detailed description is given using the embodiments of the two application scenarios of immediate charging mode and scheduled charging mode.

[0077] In one embodiment, when the target charging mode of step S20 is the immediate charging mode, the step of generating the optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes:

[0078] S204, generating the optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information; wherein the immediate charging parameter optimization model can be understood as an optimization model constructed with the plug-in time as the starting charging time and charging to reach the target power value in the shortest possible time as the optimization target, that is, the immediate charging parameter optimization model is constructed with minimizing the charging time as the optimization target, and the objective function of the immediate charging parameter optimization model is expressed as:

[0079]

[0080] In the formula, T represents the charging time; Soc s and Soc e They respectively represent the current battery state of charge and the target battery state of charge, and the target battery state of charge can be obtained through the vehicle charging demand set by the user's mobile terminal. If not set, the default value (for example, 80%) is selected; E represents the battery capacity; η represents the charging efficiency, and the maximum charging efficiency value can be selected according to the scenario; U and I represent the charging voltage and charging current, respectively.

[0081] In practical applications, when solving the optimal charging current based on the objective function shown in formula (1), the charging power constraint shown in formula (2) must be satisfied:

[0082]

[0083] Where P t represents the charging power of the electric vehicle at time t, and U t and I t They represent the charging voltage and charging current of the electric vehicle at time t respectively; P t,max and P t,min They respectively represent the maximum charging power and the minimum charging power of the electric vehicle at time t, which are obtained based on the device charging parameters transmitted by the power supply device through PLC communication.

[0084] It should be noted that, since constant voltage charging is generally used in actual charging, the U in the charging power of formula (2) is t The value is fixed, just make I t Satisfy 0≤I t ≤I t,maxAt the same time, considering that the charging efficiency is easily affected by temperature, in order to ensure the shortest charging time, the operating temperature of the battery can be monitored and regulated to achieve the maximum charging efficiency. For example, if η is 100% when the temperature is 25°C, the battery temperature can be controlled to remain at 25°C through relevant technologies.

[0085] In order to ensure the effectiveness of solving the expected charging current based on the immediate charging parameter optimization model obtained by equations (1) and (2), the present embodiment preferably sets the device charging parameters to include the maximum charging current, the minimum charging current, the maximum charging voltage and the minimum charging voltage; the vehicle body charging information includes the battery capacity, the allowable charging voltage, the current battery state of charge, the target battery state of charge, the cable rated current and the maximum required battery current; specifically, in step S204, the step of generating the optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information includes:

[0086] S2041. Determine a charging power constraint according to the device charging parameters; wherein the determination of the charging power constraint can be understood as determining P according to the maximum charging current, the minimum charging current in the device charging parameters and the allowable charging voltage in the vehicle body charging information. t,max and P t,min And enter the allowable charging power range at different times into formula (2).

[0087] S2042. According to the battery capacity, allowable charging voltage, current battery state of charge and target battery state of charge in the vehicle body charging information, the immediate charging parameter optimization model is solved with the charging power constraint as a constraint condition to obtain the expected charging current; wherein, the process of solving the expected charging current can be understood as taking the charging current as a variable and minimizing the charging time as a goal, and solving the immediate charging parameter optimization model based on a relevant algorithm to obtain the optimal variable value. The specific solution process is not limited here.

[0088] S2043. Obtain the minimum current value of the expected charging current and the cable rated current and the battery maximum required current in the vehicle body charging information, and generate the optimal charging parameter according to the minimum current value and the allowable charging voltage; wherein the optimal charging parameter can be understood as the most suitable charging current that is finally determined by comprehensively analyzing the charging safety problem in the actual AC charging process in combination with the cable capacity and the vehicle-side required current, and is expressed as:

[0089] I t =min{I t,max ,I cc ,I EV} (3)

[0090] In the formula, It It is represented by the demand current of the electric vehicle end and the power supply equipment end at time t, which is the minimum current value among the expected charging current, the rated current of the cable and the maximum demand current of the battery; I cc Indicates the rated current of the cable (cable current capability value) identified by the CC value at the electric vehicle end; I EV Indicates the current maximum battery demand current of the electric vehicle, which can be obtained based on the existing functions of the vehicle body and will not be described in detail here.

[0091] Through the above method steps, it is possible to calculate the optimal charging parameters based on the charging environment conditions of the power supply device (the maximum charging current, minimum charging current, maximum charging voltage and minimum charging voltage supported by the power supply device, etc.) and the electric vehicle itself based on formula (3) before starting the immediate charging to meet the immediate charging strategy of reaching the charging target value within the shortest charging time, thereby ensuring the safety and effectiveness of starting the charging in the immediate charging mode.

[0092] In one embodiment, when the target charging mode in step S20 is a scheduled charging mode, the step of generating optimal charging parameters based on a corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes:

[0093] S205. Generate the optimal charging parameters based on the corresponding scheduled charging parameter optimization model according to the device charging parameters and the vehicle body charging information; the scheduled charging parameter optimization model includes a scheduled time period optimization model with minimizing user charging costs as the optimization goal, and a time period charging parameter optimization model with minimizing grid load fluctuations as the optimization goal.

[0094] In this embodiment, the reservation period optimization model can be understood as an optimization model that takes into account the different electricity prices at different times of the day, the existence of peak price periods and valley price periods, and preferably takes the reservation charging period with the minimum charging cost as the goal to build an optimization model; specifically, in step S205, the objective function of the reservation period optimization model is expressed as:

[0095]

[0096] Among them, F1 represents the user's charging cost; B t P represents the charging price per unit of electricity at time t, which can be obtained from the power grid area price table in the equipment charging parameters; trepresents the charging power at time t, which also needs to satisfy the power constraint shown in formula (2); t1 and t2 represent the charging start time and charging end time respectively. The corresponding calculation time step can be set according to the actual application requirements, for example, set to 1 hour, that is, when the user charges, the unit electricity charging price per hour in a day in the power grid area electricity price table is calculated. It should be noted that in actual applications, t1 and t2 need to meet an implicit charging time limit. First, the user-set charging time T1 set by the user when selecting the scheduled charging mode is obtained through the mobile terminal. At the same time, the estimated charging time T2 is calculated according to the target battery charge state set by the user, and the minimum value T op As a restriction on the selection of t1 and t2 in the process of solving equation (4).

[0097] The time period charging parameter optimization model in this embodiment can be understood as taking into account the fact that based on the selection of the above-mentioned optimal charging time period, there may be a situation where the charging of electric vehicles is concentrated in a certain low-price time period of the power grid, resulting in a large charging load of electric vehicles in the regional power grid during the valley period, and then forming a new load peak during the valley period of the regional power grid load, causing load fluctuations in the regional power grid, affecting the stability of the regional power grid operation and being unfavorable to the power grid management. Preferably, the charging parameter optimization model is constructed by analyzing the volatility of the regional power grid based on the number of electric vehicle accesses in the selected scheduled charging time period. Specifically, in step S205, the objective function of the time period charging parameter optimization model is expressed as:

[0098]

[0099] In the formula,

[0100]

[0101]

[0102]

[0103] Among them, F2 represents the grid load fluctuation; represents the target charging period, which can be understood as the user's expected charging period determined based on formula (4); s (t) represents the equivalent load power at time t; P avg Indicates average load power; P load (t) and P EV (t) represent the basic load power when no electric vehicle is connected to the grid at time t and the load power when an electric vehicle is in charging state; X c (t) and P cIt represents the charging status (1 means connected and charging, 0 means connected but not charging) and charging power of electric vehicle c at time t, and N represents the total number of electric vehicles connected to the power grid in the power grid area at time t, which can be obtained from the device charging parameters transmitted by the power supply device connected to the electric vehicle.

[0104] In order to ensure the effectiveness of solving the expected charging current based on the scheduled charging parameter optimization model obtained by equations (4)-(8), the present embodiment preferably sets the device charging parameters to include the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the power grid area electricity price table, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle; the vehicle body charging information includes the battery capacity, the allowable charging voltage, the current battery state of charge, the target battery state of charge, the cable rated current and the maximum required battery current; specifically, in step S205, according to the device charging parameters and the vehicle body charging information, the step of generating the optimal charging parameters based on the corresponding scheduled charging parameter optimization model includes:

[0105] S2051. Calculate the estimated charging time according to the battery capacity, current battery state of charge and target battery state of charge in the vehicle body charging information, and obtain the minimum value between the estimated charging time and the charging time set by the user as the scheduled charging time; wherein the estimated charging time T2 is calculated based on formula (9), and the minimum value between the estimated charging time T2 and the charging time set by the user T1 is used as the scheduled charging time T op , and the charging time constraint t2-t1≤T in the solution process of equation (4) is obtained op .

[0106]

[0107] Where, T2 represents the expected charging time; Soc s and Soc e They respectively represent the current battery state of charge and the target battery state of charge, and the target battery state of charge can be obtained through the vehicle charging demand set by the user's mobile terminal. If not set, the default value (for example, 80%) is selected; E represents the battery capacity; η represents the charging efficiency, and the maximum charging efficiency value can be selected according to the scenario; P represents the preset charging power, which can be set according to actual application requirements.

[0108] S2052. Solve the reservation period optimization model according to the scheduled charging time, and the maximum charging current, minimum charging current, maximum charging voltage, minimum charging voltage and power grid area electricity price list in the device charging parameters to obtain at least one optimal scheduled charging period; wherein the optimal scheduled charging period can be understood as substituting the scheduled charging time, maximum charging current, minimum charging current, maximum charging voltage, minimum charging voltage and power grid area electricity price list into the reservation period optimization model shown in formula (4), and using the corresponding solution algorithm to obtain the reservable charging period that minimizes the user's charging cost; in actual application, the optimal scheduled charging period obtained can be one or more, which can be sent to the mobile terminal for user selection.

[0109] S2053. Send all optimal scheduled charging time periods to the corresponding vehicle-associated mobile terminal to obtain the user's expected charging time period; wherein the user's expected charging time period can be understood as the slowest satisfactory charging time period selected from all optimal scheduled charging time periods by the user based on the time information and charging cost information corresponding to all the received optimal scheduled charging time periods, combined with the start time of the next trip or other screening criteria; it should be noted that if the user does not select the charging start time (charging time period) within the specified time, the earliest time period for charging among all recommended time periods is selected by default as the user's expected charging time period; at the same time, if the optimal scheduled charging time period actually solved is one, the user can also choose whether to adopt the recommended time period or switch to immediate charging.

[0110] S2054. Solve the time period charging parameter optimization model according to the user's expected charging time period, the allowed charging voltage in the vehicle body charging information, and the device charging parameters including the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle, and obtain the scheduled expected charging current; wherein the scheduled expected charging current can be understood as substituting the user's expected charging time period, the allowed charging voltage, the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle into the time period charging parameter optimization model shown in equations (5)-(8), and using the corresponding solution algorithm to obtain the charging current that minimizes the regional power grid fluctuation.

[0111] S2055. Obtain the minimum current value of the expected charging current and the cable rated current and the battery maximum required current in the vehicle body charging information, and generate the optimal charging parameters according to the minimum current value, the allowable charging voltage and the user's expected charging period; wherein, the process of obtaining the optimal charging parameters can be understood as firstly conducting a comprehensive analysis based on the charging safety issues in the actual AC charging process, combined with the cable capacity and the vehicle-side required current, and then generating the charging parameters that need to be transmitted to the power supply device end together with the most suitable charging current demand value determined based on formula (3) together with the allowable charging voltage of the vehicle body and the user's expected charging period.

[0112] This embodiment respectively constructs an immediate charging parameter optimization model with minimizing charging time as the optimization goal, a reservation period optimization model with minimizing user charging cost as the optimization goal, and a period charging parameter optimization model with minimizing grid load fluctuation as the optimization goal, and finally obtains a reservation charging parameter optimization model, which realizes reliable selection of charging parameters under different charging modes to adapt to changes in the charging environment of the power supply equipment end and the needs of electric vehicles, and effectively improves the charging efficiency and charging safety of electric vehicles.

[0113] S30, after sending the optimal charging parameters to the power supply device, the charging task is performed according to the target charging mode and the optimal charging parameters; wherein, after the electric vehicle end generates the optimal charging parameters under different target charging modes according to the device charging parameters and vehicle body charging information obtained from the power supply device end through the above method steps, the currently calculated optimal demand current and other parameters can be sent to the power supply device through the signal PowerDeliveryReq, so as to achieve the optimal charging target; at the same time, after the power supply device end and the electric vehicle end confirm the charging parameters, Figure 5 As shown, the switch S2 on the electric vehicle side is closed, and the state of the power supply device side changes from State 2' to State 3'. By closing switches C1 and C2, energy transmission can begin, and the charging task can be performed according to the target charging mode and the corresponding optimal charging parameters: if the target charging mode is the immediate charging mode, the power supply device directly transmits energy to the electric vehicle according to the received optimal charging parameters; if the target charging mode is the scheduled charging mode, the power supply device stores the received optimal charging parameters and starts charging according to the corresponding charging current demand value based on the user's expected charging period.

[0114] In addition, considering that the charging environment and electric vehicle demand at the power supply equipment end may change in real time during the actual charging process, if the optimal charging parameters at the start-up charging time are used consistently for continuous charging, there may be low charging efficiency or charging safety problems. In order to facilitate the real-time perception of the changes in the charging environment and electric vehicle demand at the power supply equipment end, and timely adaptively adjust the charging parameters based on the changes, so as to ensure the charging efficiency in real time, it can also avoid the safety hazards caused by the lag in the discovery of problems in the charging process. In this embodiment, preferably, during the entire charging process, the electric vehicle end communicates with the power supply equipment end in real time PLC, the electric vehicle end periodically sends a PowerDeliveryReq signal to the power supply equipment end, and the electric vehicle end obtains the current allowed charging current range and charging voltage range of the power supply equipment in real time through the PowerDeliveryRes signal replied by the power supply equipment end (the load rate of the power grid is different in different time periods, resulting in different restrictions on the charge, and then the current range and voltage range allowed for charging at the power supply equipment end will also change) and other equipment charging parameter information, and generates the optimal charging parameters based on the preset charging parameter optimization model under the corresponding charging mode according to the equipment charging parameter information combined with the vehicle body charging information, so as to realize the real-time intelligent regulation of the charging power of the electric vehicle during the charging process according to the real-time charging demand changes. Specifically, in step S30, the method further includes:

[0115] S301. During the charging process, the latest charging parameters are periodically obtained from the power supply device through the PLC signal, and real-time optimal charging parameters are generated based on the latest charging parameters and the latest vehicle body charging information based on the corresponding preset charging parameter optimization model, and the real-time optimal charging parameters are sent to the power supply device to adjust the charging power in real time.

[0116] In actual applications, an electric vehicle that has started charging periodically monitors and obtains body charging information to determine whether the expected charging target has been reached. If the expected charging target has not been reached, a PowerDeliveryReq signal is sent to the power supply device according to a preset communication frequency to perceive changes in device charging parameters such as the allowable charging current range and charging voltage range on the power supply device side in real time according to the PowerDeliveryRes signal returned by the power supply device, and based on this, the optimal required current and other parameters in the corresponding charging mode are obtained and sent to the power supply device to achieve adaptive control of charging power in the AC charging process: When the electric vehicle starts the charging process in the immediate charging mode, the latest charging parameters and body charging information obtained in real time during the charging process are used. The expected charging current is solved based on the immediate charging parameter optimization model shown in formula (1) and formula (2), and the most suitable charging current demand value is obtained based on the processing shown in formula (3) according to the obtained expected charging current, and the required optimal charging parameters are generated accordingly for negotiation with the power supply equipment; when the electric vehicle starts the charging process in the scheduled charging mode, the expected charging current is solved based on the time period charging parameter optimization model shown in formulas (5)-(8) according to the latest charging parameters and vehicle body charging information obtained in real time during the charging process, and the most suitable charging current demand value is obtained based on the processing shown in formula (3) according to the obtained expected charging current, and the required optimal charging parameters are generated accordingly for negotiation with the power supply equipment.

[0117] At the same time, the power supply equipment will periodically detect grid restrictions, user operation instructions, and whether the electric vehicle has any abnormalities that require shutdown, to ensure the efficiency and safety of the charging process. When the electric vehicle or the power supply equipment detects that the charging end conditions are met, it will automatically end the charging process after communicating with the other party, that is, the electric vehicle turns on the S2 switch, and the state of the power supply equipment changes from State 3' to State 2'.

[0118] In addition, in order to meet the actual charging needs, meet the adaptive management and control in various charging scenarios, and improve the flexibility of power supply control, this embodiment preferably allows the switching of charging modes and the adjustment of charging time in the scheduled charging mode before the scheduled charging is started: when the electric vehicle using the scheduled charging mode has not started charging, the charging mode can also be switched through the vehicle-associated mobile terminal. When the target charging mode of the electric vehicle is switched from the scheduled charging mode to the immediate charging mode, it is necessary to generate the optimal charging current according to the optimal charging parameter acquisition scheme before the immediate charging mode is started, and start charging immediately accordingly, and during the charging process, according to the latest charging parameters and vehicle body charging information obtained in real time, the charging power in the charging process is intelligently optimized and regulated based on the corresponding immediate charging parameter optimization model; at the same time, when the electric vehicle using the scheduled charging mode has started charging, the start time of the next trip (adjustment of the charging end time) can be revised through the vehicle-associated mobile terminal to re-trigger the charging parameter optimization process, and according to this revision, combined with the latest charging parameters and vehicle body charging information obtained in real time, the charging power in the charging process is intelligently optimized and regulated based on the time period charging parameter optimization model.

[0119] The electric vehicle provided in the embodiment of the present invention interacts with the power supply equipment for charging services, charging parameters and other data through a PLC signal coupled to a charging control guide signal, and the electric vehicle generates optimal charging parameters based on the real-time acquired equipment charging parameters and vehicle body charging information, combined with the charging strategy optimization target under different charging modes, and feeds back to the power supply equipment to realize a technical solution for adaptive intelligent control of charging power. Compared with the prior art, it can perceive the changes in the charging environment of the power supply equipment and the needs of the electric vehicle in real time during the AC charging process, adaptively adjust the charging parameters of the electric vehicle end, and realize intelligent management of the AC charging process of the electric vehicle, which can not only effectively improve the charging efficiency and charging safety of the electric vehicle, but also realize personalized management of charging needs and improve the flexibility of charging control.

[0120] It should be noted that although the steps in the above flowchart are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders.

[0121] In one embodiment, an electric vehicle is provided, which exchanges data with a power supply device via a PLC signal coupled to a charging control guidance signal; the electric vehicle includes an adaptive charging control device; the adaptive charging control device implements the steps of the above method when executing charging control.

[0122] In summary, an embodiment of the present invention provides an adaptive charging control method and system for an electric vehicle, wherein the adaptive charging control method for an electric vehicle implements data interaction between the electric vehicle and the power supply device through a PLC signal coupled to a charging control guide signal, obtains the communication address of the power supply device after confirming the connection with the power supply device, and establishes a communication connection according to the communication address, sequentially executes a service information interaction process and a charging parameter acquisition process including application protocol request, session establishment, service acquisition and identification verification, and obtains device charging parameters, target charging mode and vehicle body charging information in response to a charging parameter acquisition response signal, and based on the device charging parameters, target charging mode and vehicle body charging information, a preset charging optimization target is constructed based on the corresponding device charging parameters and vehicle body charging information as optimization conditions and based on different target charging modes. The charging parameter optimization model generates optimal charging parameters, and after sending the optimal charging parameters to the power supply equipment, the charging task is performed according to the target charging mode and the optimal charging parameters. During the charging process, the latest charging parameters are periodically obtained from the power supply equipment through the PLC signal, and according to the latest charging parameters and the latest vehicle body charging information, the real-time optimal charging parameters are generated based on the corresponding preset charging parameter optimization model and sent to the power supply equipment to adjust the charging power in real time. The technical solution can sense the changes in the charging environment of the power supply equipment and the needs of the electric vehicle in real time during the AC charging process, adaptively adjust the charging parameters of the electric vehicle end, and realize the intelligent management of the AC charging process of the electric vehicle. It can not only effectively improve the charging efficiency and charging safety of the electric vehicle, but also realize the personalized management of charging needs and improve the flexibility of charging control.

[0123] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be directly referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-mentioned embodiments only express several preferred implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principle of the present invention, and these improvements and substitutions should also be regarded as the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the protection scope of the claims.

Claims

1. An adaptive charging control method for an electric vehicle, characterized in that: Applicable to an electric vehicle that performs data interaction with a power supply device through a PLC signal coupled to a charging control pilot signal; the method comprises the following steps: S10, after confirming the connection with the power supply device, obtaining the communication address of the power supply device, establishing a communication connection according to the communication address, and executing a service information interaction process; the service information interaction process is used to perform various service information interactions with the power supply device, including application protocol request, session establishment, service acquisition and identification verification; S20, executing a charging parameter acquisition process to acquire device charging parameters, a target charging mode, and vehicle body charging information, and generating optimal charging parameters based on a corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode, and the vehicle body charging information; the preset charging parameter optimization model is an expected charging current optimization model constructed based on charging optimization targets of different target charging modes and taking the device charging parameters and the vehicle body charging information as optimization conditions; S30: After sending the optimal charging parameters to the power supply device, execute the charging task according to the target charging mode and the optimal charging parameters.

2. The adaptive charging control method for an electric vehicle according to claim 1, characterized in that: In step S20, the charging parameter acquisition process is executed, and the steps of acquiring the target charging mode include: S201, sending a charging mode request to a corresponding vehicle-associated mobile terminal and starting a corresponding request response timer; S202: when the request response timer has not timed out and a corresponding charging mode request response is received, setting the target charging mode according to the charging mode request response; S203: When the request response timer times out and the charging mode request response is not received, setting the target charging mode to a reserved charging mode.

3. The adaptive charging control method for an electric vehicle according to claim 1, characterized in that: In step S20, the target charging mode includes an immediate charging mode and a scheduled charging mode. When the target charging mode is the immediate charging mode, the step of generating optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes: S204, generating the optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information; the immediate charging parameter optimization model is constructed with minimizing the charging time as the optimization goal; the objective function of the immediate charging parameter optimization model is expressed as: In the formula, T represents the charging time; Soc s and Soc e They represent the current battery state of charge and the target battery state of charge respectively; E represents the battery capacity; η represents the charging efficiency; U and I represent the charging voltage and charging current respectively.

4. The adaptive charging control method for an electric vehicle according to claim 3, characterized in that: The device charging parameters include the maximum charging current, the minimum charging current, the maximum charging voltage and the minimum charging voltage; the vehicle body charging information includes the battery capacity, the allowable charging voltage, the current battery state of charge, the target battery state of charge, the cable rated current and the maximum required battery current; In step S204, the step of generating optimal charging parameters based on the corresponding immediate charging parameter optimization model according to the device charging parameters and the vehicle body charging information includes: S2041. Determine a charging power constraint according to the device charging parameter; S2042, according to the battery capacity, the allowable charging voltage, the current battery state of charge and the target battery state of charge in the vehicle body charging information, solving the immediate charging parameter optimization model with the charging power constraint as a constraint condition to obtain the expected charging current; S2043. Obtain the expected charging current and the minimum current value of the cable rated current and the battery maximum required current in the vehicle body charging information, and generate the optimal charging parameter according to the minimum current value and the allowable charging voltage.

5. The adaptive charging control method for an electric vehicle according to claim 1, characterized in that: In step S20, the target charging mode includes an immediate charging mode and a scheduled charging mode. When the target charging mode is the scheduled charging mode, the step of generating optimal charging parameters based on the corresponding preset charging parameter optimization model according to the device charging parameters, the target charging mode and the vehicle body charging information includes: S205. Generate the optimal charging parameters based on the corresponding scheduled charging parameter optimization model according to the device charging parameters and the vehicle body charging information; the scheduled charging parameter optimization model includes a scheduled time period optimization model with minimizing user charging costs as the optimization goal, and a time period charging parameter optimization model with minimizing grid load fluctuations as the optimization goal.

6. The adaptive charging control method for an electric vehicle according to claim 5, characterized in that: In step S205, the objective function of the reservation time period optimization model is expressed as: Among them, F1 represents the user's charging cost; B t P represents the charging price per unit of electricity at time t; t represents the charging power at time t; t1 and t2 represent the charging start time and charging end time respectively.

7. The adaptive charging control method for an electric vehicle according to claim 6, characterized in that: In step S205, the objective function of the time period charging parameter optimization model is expressed as: In the formula, Among them, F2 represents the grid load fluctuation; Indicates the target charging period; P s (t) represents the equivalent load power at time t; P avg Indicates average load power; P load (t) and P EV (t) represent the basic load power when no electric vehicle is connected to the grid at time t and the load power when an electric vehicle is in charging state; X c (t) and P c represents the charging status and charging power of electric vehicle c at time t; N represents the total number of electric vehicles connected to the power grid in the power grid area at time t.

8. The adaptive charging control method for an electric vehicle according to claim 7, characterized in that: The equipment charging parameters include the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the power grid area electricity price list, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle; the vehicle body charging information includes the battery capacity, the allowed charging voltage, the current battery state of charge, the target battery state of charge, the cable rated current and the maximum required battery current; In step S205, the step of generating optimal charging parameters based on the corresponding scheduled charging parameter optimization model according to the device charging parameters and the vehicle body charging information includes: S2051, calculating an estimated charging time according to the battery capacity, current battery state of charge and target battery state of charge in the vehicle body charging information, and obtaining a minimum value between the estimated charging time and the charging time set by the user as the scheduled charging time; S2052, solving the reservation period optimization model according to the scheduled charging duration, the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage and the power grid area electricity price table in the device charging parameters, and obtaining at least one optimal scheduled charging period; S2053, sending all optimal scheduled charging time periods to the corresponding vehicle-associated mobile terminal to obtain the user's desired charging time period; S2054, solving the charging parameter optimization model for the time period according to the user's expected charging time period, the allowed charging voltage in the vehicle body charging information, and the device charging parameters including the maximum charging current, the minimum charging current, the maximum charging voltage, the minimum charging voltage, the number of electric vehicles connected to the power grid area, and the charging power and charging status of each electric vehicle, to obtain the scheduled expected charging current; S2055. Obtain the minimum current value among the expected charging current and the cable rated current and the maximum battery demand current in the vehicle body charging information, and generate the optimal charging parameters according to the minimum current value, the allowed charging voltage and the user's expected charging period.

9. The adaptive charging control method for an electric vehicle according to claim 1, characterized in that: In step S30, the method further includes: S301. During the charging process, the latest charging parameters are periodically obtained from the power supply device through the PLC signal, and real-time optimal charging parameters are generated based on the latest charging parameters and the latest vehicle body charging information based on the corresponding preset charging parameter optimization model, and the real-time optimal charging parameters are sent to the power supply device to adjust the charging power in real time.

10. An electric vehicle, wherein the electric vehicle exchanges data with a power supply device via a PLC signal coupled to a charging control pilot signal, characterized in that: It comprises an adaptive charging control device; when the adaptive charging control device performs charging control, the steps of the method described in any one of claims 1 to 9 are implemented.

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