Cost-optimized power battery charging control method and system

Abstract

The application provides a power battery charging control method and system based on cost optimization, relates to the technical field of power battery charging, and specifically includes the following steps: obtaining an expected charging time period set by a user to obtain an expected charging duration; obtaining a time-of-use electricity price, and obtaining electricity prices of different time periods based on the expected charging time period; obtaining charging electric energy required by the power battery, and obtaining actual required charging durations and charging electric energy of different time periods based on a charging electric energy curve of the power battery; and selecting an optimal charging time period based on the electricity prices and the charging electric energy of different time periods, and automatically outputting a charger relay control signal with the optimal charging cost as the target. The application takes the optimal power battery charging cost as a design target based on electricity prices of different regions and different time periods, controls charging time and duration through a power battery charging device, and makes the charging cost of an electric power product of a user lowest.

Description

Technical Field

[0001] This invention belongs to the field of power battery charging technology, and particularly relates to a power battery charging control method and system based on optimal cost. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] With the increasing number of electrified products, the burden on the power grid is becoming heavier and heavier, requiring adjustments to electricity prices at different times, optimization of the charging system, and ensuring the stable operation of the power grid. As energy storage or power supply components for electrified products such as electric vehicles, ships, and airplanes, disorderly charging of power batteries will inevitably cause problems such as voltage fluctuations, harmonics, and supply-demand imbalances in the power grid.

[0004] To address this, power supply departments have begun to consider adopting orderly charging strategies and methods, macroscopically altering charging prices at different times to influence users' charging timing or behavior, thus avoiding peak-hour charging congestion or off-peak periods when no one is charging. For example, patents CN110443415B "A Multi-Objective Optimization Scheduling Method for Electric Vehicle Charging Stations Considering Dynamic Electricity Pricing Strategies" and CN110415016A "A Charging Price Setting Strategy Based on Optimal Charging and Discharging Strategies" both optimize charging prices in the power supply network to macroscopically guide users' charging behavior, reduce the interaction power and its fluctuations between the power grid and charging stations, improve the stability of the power network, and ensure the virtuous cycle of the power grid.

[0005] Therefore, existing technologies primarily regulate the charging behavior of power batteries from a macroscopic perspective, without considering the microscopic charging costs for users, and thus fail to achieve optimal charging costs at the user level. Furthermore, existing power battery charging control devices enable plug-and-charge functionality, but electricity prices vary at different times, meaning that charging costs largely depend on the user's charging schedule. Moreover, since these operations are based on human control, they also cannot achieve optimal charging costs. Summary of the Invention

[0006] To overcome the shortcomings of the prior art, this invention provides a power battery charging control method and system based on optimal cost. Based on electricity prices in different regions and at different times, and with the goal of optimizing power battery charging cost, the method regulates the charging timing and duration through the power battery charging device, thereby minimizing the charging cost for users' electric power products.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] The first aspect of this invention provides a power battery charging control method based on optimal cost;

[0009] A cost-optimal power battery charging control method is used for charger control of the charging period, including:

[0010] Obtain the user's desired charging time period to get the desired charging duration;

[0011] Obtain the time-of-use electricity price from the power grid, and based on the expected charging time period, obtain the electricity price for different time periods;

[0012] The charging energy required by the power battery is obtained, and based on the charging energy curve of the power battery, the actual charging time and charging energy at different times are obtained.

[0013] Based on electricity prices and charging energy at different times, with the goal of minimizing charging costs, the system selects the optimal charging time and automatically outputs a charger relay control signal.

[0014] Furthermore, the desired charging time period is the charging start time and charging end time that the user sets for the charger via wired or wireless means.

[0015] Furthermore, the acquisition of the grid time-of-use electricity price specifically involves the electric vehicle charger acquiring the real-time time-of-use electricity price of the area where the charger is located via wired or wireless transmission.

[0016] Furthermore, the process of obtaining electricity prices for different time periods based on the desired charging time period is as follows:

[0017] The desired charging period is discretized into multiple moments using a preset time interval;

[0018] The average of the time-of-use electricity prices at two adjacent moments is used as the electricity price for the period between the two adjacent moments, thus obtaining the electricity price for different periods.

[0019] Furthermore, the process of obtaining the charging energy required for the power battery specifically involves: electrical interconnection between the charger and the power battery to obtain the remaining energy value and the fully charged energy value of the power battery.

[0020] Furthermore, the charging energy curve based on the power battery yields the actual required charging time and charging energy at different times, specifically as follows:

[0021] Based on the remaining battery energy and the fully charged energy, calculate the charging energy required to fully charge the power battery;

[0022] Based on the charging energy curve of the power battery, and the charging energy required to fully charge the power battery, the actual charging time required is estimated.

[0023] Using a preset time interval, the actual required charging time is discretized to obtain the charging energy at different time periods.

[0024] Furthermore, based on electricity prices and charging energy at different times, and with the goal of optimizing charging costs, the optimal charging time period is selected, and a charger relay control signal is automatically output. Specifically:

[0025] When the desired charging time is greater than the actual required charging time, multiple time periods are selected consecutively within the desired charging time period, and the sum of the durations of the multiple time periods cannot be less than the actual required charging time.

[0026] Calculate the charging cost based on the electricity price and charging energy corresponding to the selected multiple time periods;

[0027] Choose the time period with the lowest charging cost as the optimal charging time.

[0028] During the optimal charging period, the charger outputs a relay activation signal, and during other periods, it outputs a relay deactivation signal.

[0029] The second aspect of the present invention provides a power battery charging control system based on optimal cost.

[0030] Based on a cost-optimal power battery charging control system, this system controls the charging period for the charger and includes a desired acquisition module, an electricity price acquisition module, an energy acquisition module, and an optimal selection module.

[0031] The expectation acquisition module is configured to: acquire the user-set expected charging time period and obtain the expected charging duration;

[0032] The electricity price acquisition module is configured to: acquire the grid time-of-use electricity price, and obtain the electricity price for different time periods based on the expected charging time period;

[0033] The power acquisition module is configured to: acquire the charging power required by the power battery, and based on the charging power curve of the power battery, obtain the actual required charging time and the charging power at different times.

[0034] The optimal selection module is configured to select the optimal charging period based on the electricity price and charging energy at different times, with the goal of minimizing charging costs, and automatically output the charger relay control signal.

[0035] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the cost-optimal power battery charging control method as described in the first aspect of the present invention.

[0036] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the cost-optimal power battery charging control method as described in the first aspect of the present invention.

[0037] The above one or more technical solutions have the following beneficial effects:

[0038] This invention uses parameters such as the time-of-use electricity price of the power grid, the charging start time and charging end time set by the user, and the charging start energy and full charge energy fed back by the power battery BMS management system to realize real-time charging strategy control of electric vehicles, ultimately ensuring the optimal charging cost for users and reducing the energy cost output of electric vehicle users.

[0039] This invention is based on a cost-optimal power battery charging control method, which avoids problems such as voltage fluctuations, harmonics, and supply-demand imbalances in the power grid caused by disordered charging of electric products. It takes into account the charging needs of different regions, and the power station or power grid department implements time-of-use pricing to macro-regulate users' charging behavior, avoids peak-hour concentrated charging or off-peak unattended charging, and achieves stable power supply from the power grid.

[0040] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0041] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0042] Figure 1 The first embodiment is a block diagram illustrating the principle of optimal charging cost for electric vehicles.

[0043] Figure 2 This is a flowchart of the method in the first embodiment.

[0044] Figure 3 This is the time-of-use electricity price curve for the first embodiment.

[0045] Figure 4 The charging energy curve of the power battery in the first embodiment.

[0046] Figure 5 The flowchart shows the optimal control process for power battery charging cost in the first embodiment.

[0047] Figure 6 This is a system structure diagram of the second embodiment. Detailed Implementation

[0048] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0049] With the increasing number of electric products, the burden on the power grid is becoming heavier, necessitating adjustments to electricity prices at different times, optimization of the charging system, and ensuring stable grid operation. Furthermore, differences in electricity consumption in different regions will lead to differences in regional charging prices. Based on electricity prices in different regions and at different times, with the goal of optimizing the charging cost of power batteries, the charging timing and duration are controlled through the power battery charging device to minimize the charging cost for users' electric products.

[0050] Example 1

[0051] This embodiment discloses a power battery charging control method based on optimal cost;

[0052] The principle block diagram of the optimal charging cost for electric vehicles is as follows: Figure 1 As shown, it mainly includes the power grid, charger, and electric vehicle for power supply. The charger control board wirelessly receives the time-of-use electricity price, the user-set desired charging time, and the electrical energy fed back by the electric vehicle power battery BMS management system in real time from the power grid. With the optimal charging cost as the control objective, it outputs control signals to turn the relay on or off, thereby realizing the on / off switching of the electric vehicle power battery's high-voltage DO+ or DO-, and finally achieving the optimal cost charging of the power battery.

[0053] Figure 2 This is a flowchart of a cost-optimal power battery charging control method, such as... Figure 2 As shown, a cost-optimal power battery charging control method is used for charger control of the charging period, including:

[0054] Step S1: Obtain the user's desired charging time period to get the desired charging duration.

[0055] Specifically, the user sets the charging start time T0 and charging end time Tn of the charger via wired or wireless means, then the desired charging period is [T0-Tn] and the desired charging duration is D. 期望 =Tn-T0.

[0056] Step S2: Obtain the time-of-use electricity price of the power grid, and obtain the electricity price for different time periods based on the expected charging time period.

[0057] The time-of-use electricity price curve of the power grid is as follows Figure 3 As shown, different time periods correspond to different electricity prices, so the calculation cost is optimal. First, we need to obtain the electricity price for each time period within the desired charging time period.

[0058] Specifically, the charger obtains the real-time time-of-use electricity price of the area where the charger is located via wired or wireless transmission, and discretizes the time-of-use electricity price at 1-hour intervals, as follows:

[0059] The expected charging time period between T0 and Tn is discretized into n equal parts with a 1-hour interval. Based on the real-time time-of-use electricity price, the electricity price at time T0 is P0, at time T1 is P1, ... at time Tn-1 is Pn-1, and at time Tn is Pn. The electricity price for each time period is the average of the electricity prices at each time. The final electricity prices for different time periods are shown in Table 1.

[0060] Table 1 Electricity prices at different times

[0061] Charging period T1-T0 T2-T1 、、、、、、 Tn-1-Tn-2 Tn-Tn-1 Electricity price (P0+P1) / 2 (P1+P2) / 2 、、、、、、 (Pn-2+Pn-1) / 2 (Pn-1+Pn) / 2

[0062] For example: A user plans to start charging their electric vehicle at 12:00 and expects it to be fully charged by 18:00 after get off work. This means the electric vehicle has a 6-hour expected charging time. The expected charging time between 12:00 and 18:00 is then discretized into 6 equal parts. The electricity prices for different time periods are shown in Table 2.

[0063] Table 2 Examples of electricity prices for different time periods

[0064] Charging period 12:00-13:00 13:00-14:00 、、、、、、 16:00-17:00 17:00-18:00 Electricity price <![CDATA[(P0+P1) / 2]]> <![CDATA[(P1+P2) / 2]]> 、、、、、、 <![CDATA[(P4+P5) / 2]]> <![CDATA[(P5+P6) / 2]]>

[0065] Step S3: Obtain the charging energy required by the power battery, and based on the charging energy curve of the power battery, obtain the actual required charging time and the charging energy at different times.

[0066] After obtaining the electricity price for each period within the desired charging timeframe, it is also necessary to obtain the charging energy of the power battery for each period. The power battery charging energy curve is shown below. Figure 3 As shown, different charging times correspond to different charging energy, which means that the charging efficiency of the power battery is different at each time. Therefore, given that the electricity price is different at different times within the expected charging period, choosing the appropriate time to start charging is the only way to achieve the optimal cost.

[0067] Specifically, firstly, the charger and the power battery are electrically interconnected to obtain the remaining energy value q0 and the fully charged energy value qm of the power battery. Then, the expected charging energy q required to fully charge the power battery is calculated as qm - q0. Based on the charging energy corresponding to different charging times in the power battery charging energy curve, the actual charging time D required to complete the expected charging energy q can be obtained. 实需We can also obtain the energy as q0 for 0 hours of charging, q1 for 1 hour of charging, ..., qm-1 for m-1 hours of charging, and qm for m hours of charging. Furthermore, we can obtain the charging energy as q1-q0 for the 0-1 time interval, q2-q1 for the 1-2 time interval, and qm-qm-1 for the (m-1)-m time interval. The final energy corresponding to the m charging time intervals is shown in Table 3.

[0068] Table 3 Charging energy at different time periods

[0069] Charging period 0-1 1-2 、、、、、、 (m-2)-(m-1) (m-1)-m Charging power <![CDATA[q1-q0]]> <![CDATA[q2-q1]]> 、、、、、、 <![CDATA[q m-1 -q m-2 ]]> <![CDATA[q m -q m-1 ]]>

[0070] Step S4: Based on the electricity price and charging energy at different times, with the goal of minimizing charging costs, select the optimal charging time period and automatically output the charger relay control signal.

[0071] The charger calculates the charging cost by multiplying the electricity price and the energy available in different time periods. It then finds the minimum charging cost, which is the optimal charging time period. In turn, it outputs charging control signals for the power battery at different times, driving the power battery's high-voltage relay to turn on and off.

[0072] Specifically, there are two situations:

[0073] Scenario 1: When the user's expected charging time D 期望 No more than D, the actual charging time required for the power battery to be fully charged. 实需 In cases where the battery cannot be fully charged even if it is charged for the entire expected charging time, electric vehicles can be plugged in and charged immediately. There is no need to optimize or control the charging time, and this is not considered as the optimal charging cost.

[0074] The second scenario: when the user's expected charging time D 期望 The charging time D required to fully charge the power battery is greater than the actual charging time required. 实需 If the battery is fully charged within the user's desired charging time, there will be a period of idle time after the battery is fully charged. This embodiment utilizes this idle time to optimize and control the charging time, specifically:

[0075] Expected charging time D 期望 Within n time intervals, m consecutive time intervals are selected, where m is the actual required charging time D. 实需Given the number of time periods, there are A(n-m+2,2) ways to choose them. For each choice, the electricity price and energy for the m time periods are multiplied by a vector. These A(n-m+2,2) choices result in A(n-m+2,2) charging costs. Comparing these costs yields the minimum value, and the corresponding m consecutive time periods are the optimal charging periods. The charger outputs a control signal for the corresponding time period, which is the relay's on signal; other time periods are the relay's off signal. The optimal charging cost is calculated as follows:

[0076] (1) Within n time intervals, if m consecutive time intervals are selected, there are A(n-m+2,2) ways to select them, which in turn leads to A(n-m+2,2) different electricity prices. The electricity price expression A for the A(n-m+2,2) selection methods is A(n-m+2,2) rows and m columns, where each row represents one selection method. Specifically, A is:

[0077]

[0078] (2) Represent the charging energy of m charging periods as an m-row, 1-column vector B, with the following expression:

[0079] B = [q1-q0q2-q1…q] m-1 -q m-2 q m -q m-1 ] T

[0080] (3) Calculate the expected charging time D 期望 The charging cost for n time intervals and m charging periods is expressed as:

[0081] Y = A * B

[0082] Where Y is a charging cost vector of A(n-m+2,2) rows and 1 column, with each row representing the charging cost corresponding to each row in the electricity price expression A, that is, the charging cost corresponding to each selected charging period.

[0083] (4) By comparing the costs Y of A(n-m+2,2) types of charging using the golden section method, the minimum charging cost Ymin is finally obtained, and the group of electricity price combinations Amin is extracted. The expression is assumed to be:

[0084] Ymin = Find_min(Y)

[0085]

[0086] (5) Based on the optimal cost charging price combination Amin, output the charger relay control signal, where 1 represents the relay being on (charging state) and 0 represents the relay being off (charging stopped). Amin represents the charging period from T0 to Tn-m-1 (charging stops) and from Tn-m to Tn (charging continues). The corresponding charging period expression is:

[0087]

[0088] in, For T0, T1, T2, T n The relay is turned off at any time, stopping charging; For T n-m T n-m+1 T n-m+2 T n-2 T n-1 The relay is activated at all times to initiate charging.

[0089] (6) Output the control signal of the charger, which is then driven by the built-in drive module of the charger control board to turn the relay on or off, thereby achieving the optimal charging cost for the electric vehicle power battery.

[0090] To better understand the optimal method for controlling the charging cost of power batteries, refer to... Figure 5 The flowchart for optimal control of power battery charging cost, with Figure 2 and Figure 3 Assuming the data is used for illustration, the steps are as follows:

[0091] Step 1: The charger obtains the time-of-use electricity price from the grid and performs discretization processing.

[0092] Assuming charging starts at 12:00 and ends at 18:00, the expected charging time is 6 hours to fully charge the electric vehicle. Figure 2 The corresponding time-of-use electricity prices are shown in Table 4:

[0093] Table 4. Example of Time-of-Use Electricity Pricing

[0094] Charging period 12:00-13:00 13:00-14:00 14:00-15:00 15:00-16:00 16:00-17:00 17:00-18:00 Electricity price 2.2 2.0 1.9 1.8 1.9 2.2

[0095] Step 2: The charger acquires charging energy and performs discretization processing on the charging energy.

[0096] Assuming it takes 4 hours to fully charge an electric vehicle, the initial energy (q0) is 7 kWh, and the total energy (q4) after charging is 30 kWh. Figure 3 The corresponding electrical energy is shown in Table 5:

[0097] Table 5 Examples of Electricity Consumption by Time of Day

[0098] Charging period 0-1 1-2 2-3 3-4 Electricity 18 2 2 1

[0099] Step 3: Calculate the minimum charging cost and determine the charging time.

[0100] Based on the electricity price and electricity energy data, with n = 6 and m = 4, there are a total of 6 charging cost prices (A(n - m + 2, 2)), and the prices are as follows:

[0101] Y1 = 2.2 * 18 + 2.0 * 2 + 1.9 * 2 + 1.8 * 1 = 49.2

[0102] Y2 = 2.2 * 18 + 1.9 * 2 + 1.8 * 2 + 1.9 * 1 = 48.9

[0103] Y3 = 2.2 * 18 + 1.8 * 2 + 1.9 * 2 + 2.2 * 1 = 49.2

[0104] Y4 = 2.0 * 18 + 1.9 * 2 + 1.8 * 2 + 1.9 * 1 = 45.3 <000032�>Y5 = 2.0 * 18 + 1.8 * 2 + 1.9 * 2 + 2.2 * 1 = 45.6

[0106] Y6 = 1.9 * 18 + 1.8 * 2 + 1.9 * 2 + 2.2 * 1 = 43.8

[0107] The price ranking is: Y6 < Y4 < Y5 < Y2 < Y3 = Y1. That is, charging starts at 14:00 and ends at 18:00. The charging relay is off from 12:00 to 14:00 and on from 14:00 to 16:00. The output control signal is:

[0108] Csignal = [0 12:0 0 13: 1 14:0 1 15:0 1 16:0 1 17: 0 18:

[0109] The present invention proposes a charging control method for power batteries based on cost optimization. The charger receives information such as the time-of-use electricity price of the power grid, the charging start / end time given by the user, and the charging start electricity energy / full state electricity energy sent by the power battery BMS management system, and takes the optimal charging cost as the control target to adjust the charging time of the electric vehicle in real time, realizing the optimal charging of the electric vehicle at the user level. [[ID=4,7]]

[0110] Embodiment 2

[0111] This embodiment discloses a charging control system for power batteries based on cost optimization;

[0112] As Figure 6As shown, a cost-optimal power battery charging control system is used for charger control of charging periods, including a desired acquisition module, an electricity price acquisition module, an energy acquisition module, and an optimal selection module:

[0113] The expectation acquisition module is configured to: acquire the user-set expected charging time period and obtain the expected charging duration;

[0114] The electricity price acquisition module is configured to: acquire the grid time-of-use electricity price, and obtain the electricity price for different time periods based on the expected charging time period;

[0115] The power acquisition module is configured to: acquire the charging power required by the power battery, and based on the charging power curve of the power battery, obtain the actual required charging time and the charging power at different times.

[0116] The optimal selection module is configured to select the optimal charging period based on the electricity price and charging energy at different times, with the goal of minimizing charging costs, and automatically output the charger relay control signal.

[0117] Example 3

[0118] The purpose of this embodiment is to provide a computer-readable storage medium.

[0119] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the cost-optimal power battery charging control method as described in Embodiment 1 of this disclosure.

[0120] Example 4

[0121] The purpose of this embodiment is to provide an electronic device.

[0122] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the cost-optimal power battery charging control method as described in Embodiment 1 of this disclosure.

[0123] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A cost-optimal power battery charging control method, characterized in that, Used for chargers to control charging periods, including: Obtain the user's desired charging time period to get the desired charging duration; Obtain the time-of-use electricity price from the power grid, and based on the expected charging time period, obtain the electricity price for different time periods; The charging energy required by the power battery is obtained, and based on the charging energy curve of the power battery, the actual charging time and charging energy at different times are obtained. Based on electricity prices and charging energy at different times, and with the goal of optimizing charging costs, the optimal charging time is selected, and a charger relay control signal is automatically output, specifically: When the desired charging time is greater than the actual required charging time, multiple time periods are selected consecutively within the desired charging time period, and the sum of the durations of the multiple time periods cannot be less than the actual required charging time. The charging cost is calculated based on the electricity price and charging energy corresponding to the selected time periods, where the charging cost is the product of the electricity price and the charging energy for each time period. Choose the time period with the lowest charging cost as the optimal charging time. During the optimal charging period, the charger outputs a relay activation signal, and during other periods, it outputs a relay deactivation signal.

2. The cost-optimal power battery charging control method as described in claim 1, characterized in that, The desired charging time period is the charging start and end time that the user sets for the charger via wired or wireless means.

3. The cost-optimal power battery charging control method as described in claim 1, characterized in that, The acquisition of the grid time-of-use electricity price specifically refers to: the electric vehicle charger acquiring the real-time time-of-use electricity price of the area where the charger is located through wired or wireless transmission.

4. The cost-optimal power battery charging control method as described in claim 1, characterized in that, The method for obtaining electricity prices for different time periods based on the expected charging time period is as follows: The desired charging period is discretized into multiple moments using a preset time interval; The average of the time-of-use electricity prices at two adjacent moments is used as the electricity price for the period between the two adjacent moments, thus obtaining the electricity price for different periods.

5. The cost-optimal power battery charging control method as described in claim 1, characterized in that, The process of obtaining the charging energy required for the power battery specifically involves: electrical interconnection between the charger and the power battery to obtain the remaining energy value and the fully charged energy value of the power battery.

6. The cost-optimal power battery charging control method as described in claim 5, characterized in that, The charging energy curve based on the power battery yields the actual required charging time and charging energy at different times, specifically: Based on the remaining battery energy and the fully charged energy, calculate the charging energy required to fully charge the power battery; Based on the charging energy curve of the power battery, and the charging energy required to fully charge the power battery, the actual charging time required is estimated. Using a preset time interval, the actual required charging time is discretized to obtain the charging energy at different time periods.

7. A cost-optimal power battery charging control system, characterized in that, This module is used for charger control of charging periods and includes a desired acquisition module, an electricity price acquisition module, an energy acquisition module, and an optimal selection module. The expectation acquisition module is configured to: acquire the user-set expected charging time period and obtain the expected charging duration; The electricity price acquisition module is configured to: acquire the grid time-of-use electricity price, and obtain the electricity price for different time periods based on the expected charging time period; The power acquisition module is configured to: acquire the charging power required by the power battery, and based on the charging power curve of the power battery, obtain the actual required charging time and the charging power at different times. The optimal selection module is configured to: select the optimal charging period based on electricity prices and charging energy at different times, with the goal of minimizing charging costs, and automatically output a charger relay control signal, specifically: When the desired charging time is greater than the actual required charging time, multiple time periods are selected consecutively within the desired charging time period, and the sum of the durations of the multiple time periods cannot be less than the actual required charging time. The charging cost is calculated based on the electricity price and charging energy corresponding to the selected time periods, where the charging cost is the product of the electricity price and the charging energy for each time period. Choose the time period with the lowest charging cost as the optimal charging time. During the optimal charging period, the charger outputs a relay activation signal, and during other periods, it outputs a relay deactivation signal.

8. An electronic device, characterized in that it comprises: Memory is used to store computer-readable instructions in a non-transitory manner. as well as Processor, for executing the computer-readable instructions, When the computer-readable instructions are executed by the processor, they perform the method described in any one of claims 1-6.

9. A storage medium characterized in that it non-transitory stores computer-readable instructions, wherein, When the non-transitory computer-readable instructions are executed by a computer, the instructions of the method according to any one of claims 1-6 are executed.

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