A vehicle charging planning method for a parking lot

Abstract

The application provides a vehicle charging planning method for a parking lot, and relates to the technical field of urban traffic planning.The method comprises the following steps: receiving position information, residual power, data information, cruising range information and charging demand of a target vehicle; collecting attribute information of a target parking lot, and screening a first charging pile from charging piles of the target parking lot in combination with the cruising range information of the target vehicle; classifying the first charging pile according to the charging demand of the target vehicle; and finally selecting an optimal charging pile from the charging pile classification result. The charging pile in the target parking lot that can be reached by the vehicle is effectively predicted in real time based on the charging demand of the target vehicle and the attribute information of the target parking lot, and the most reasonable optimal charging pile is screened, so that the charging demand of the target vehicle is met, and the utilization rate of the charging pile is improved.

Description

Technical Field

[0001] This invention relates to the field of urban traffic planning technology, and in particular to a vehicle charging planning method for parking lots. Background Technology

[0002] With the rapid development of technology, the fast pace of social and economic development, and the acceleration of urbanization, the emergence of electric vehicles has brought positive impacts on people's lives. Their environmental impact is relatively smaller than that of traditional cars, so their prospects are widely regarded as promising, and their ownership continues to grow.

[0003] However, electric vehicles are still in the early stages of development in my country, and some related technologies are not mature enough, such as long charging time and short driving range. This necessitates the ability to quickly find the optimal charging station in a parking lot to meet charging needs when the battery is low, thereby improving charging efficiency.

[0004] Therefore, this invention proposes a vehicle charging planning method for parking lots. Summary of the Invention

[0005] This invention provides a vehicle charging planning method for parking lots, which effectively predicts the real-time changes in the charging pile status within the target parking lot accessible to the vehicle based on the charging needs of the target vehicle and the attribute information of the target parking lot, thereby selecting the most reasonably matched optimal charging pile, which not only meets the charging needs of the target vehicle but also improves the utilization rate of the charging pile.

[0006] This invention provides a vehicle charging planning method for parking lots, comprising:

[0007] Step 1: Receive the target vehicle's location information, remaining battery power, and data information to determine the target vehicle's range and charging requirements;

[0008] Step 2: Collect the attribute information of the target parking lot and combine it with the range information of the target vehicle to select the first charging pile from the charging piles in the target parking lot.

[0009] Step 3: Classify the first charging piles according to charging demand to obtain the first classification result;

[0010] Step 4: When there is only one type of charging pile in the first classification result, select the optimal charging pile from the first charging pile;

[0011] Step 5: When there are two types of charging piles in the first classification result, obtain the candidate charging piles in each type of charging pile, and select the optimal charging pile from them.

[0012] Preferably, the attribute information of the target parking lot is collected, and combined with the driving range information of the target vehicle, the first charging pile is selected from the charging piles in the target parking lot, including:

[0013] Obtain the target parking lot attribute information;

[0014] Retrieve the location information from the target parking lot's attribute information, and based on the target vehicle's location information, average driving speed, and target vehicle's remaining range information, determine the vehicle's arrival time at the target parking lot and its real-time remaining battery power upon arrival.

[0015] Subtract the preset minimum reserve power from the real-time remaining power to obtain the first real-time power.

[0016] The first driving range is obtained based on the first real-time battery level, the average vehicle speed, and the vehicle's power consumption rate.

[0017] Identify all charging stations in the parking area that correspond to the first driving range, and construct a target charging station set;

[0018] Based on the parking and charging demand intensity in the target parking lot attribute information and the current time when the target vehicle arrives at the target parking lot, predict all idle charging piles in the target charging pile set when the vehicle arrives at the parking lot, and select the first charging pile.

[0019] Preferably, the prediction includes all available idle charging stations in the target charging station set when the vehicle arrives at the parking lot, including:

[0020] Step 01: Determine the total number M of target charging stations in the target charging station set. Simultaneously, number all target charging stations and obtain the weight value w for each target charging station. n where n∈1, 2, 3, ..., M;

[0021] Step 02: Train a prediction model based on the historical parking and charging data of the target parking lot, wherein the historical parking and charging data is related to the historical parking and charging time and the historical usage of each charging pile;

[0022] Step 03: Input the target charging pile status information of the previous moment and the current time when the vehicle arrives at the target parking lot into the prediction model, and predict the status value of each charging pile, as shown in the following formula:

[0023]

[0024] Where t represents the current time when the target vehicle arrives at the parking lot; x n(t) This represents the historical state periodic information of the nth charging pile at the same time t; K n This indicates the predicted state information of the nth charging pile at the previous moment. The error coefficient is represented as the calculated value, and its range is (0, e). -3 );w n This represents the weight value of the nth charging pile, with a value range of (0, 1), n∈1, 2, 3, ..., M; This represents the predicted state value of the nth charging pile;

[0025] The predicted state value is judged based on the preset standard value;

[0026] When the predicted state value is not greater than the preset standard value, the corresponding target charging pile is determined to be an idle charging pile.

[0027] Preferably, the weight value w for each target charging station is obtained. n ,include:

[0028] Step 11: Construct a fuzzy factor set A = (a1, a2, ... a m ), where a1 represents the first factor influencing driver preference; a2 represents the second factor influencing driver preference; a m This represents the m-th factor influencing driver preference;

[0029] Step 12: Create evaluation matrix B, where (b n1 ,b n2 ,…,b nm ) represents the evaluation vector of the nth charging pile, where n ranges from [1, M]; b nj Represents the evaluation vector (b) n1 ,b n2 ,…,b nm The value of the j-th factor influencing driver preference in (), where j ranges from [1, m];

[0030] Step 13: Normalize the evaluation matrix B to define the fuzzy comprehensive evaluation matrix R = (r nj ) M×m , where r nj This represents the fuzzy evaluation of the j-th factor for the n-th charging pile;

[0031] Step 14: Define the weights of the charging feedback collected from several drivers with different driving experiences to obtain a feedback weight matrix;

[0032] Step 15: After removing the maximum and minimum weight values ​​from each column of the feedback weight matrix, calculate the average of the remaining weights in the corresponding column to obtain the average weight vector.

[0033] Step 16: Combine the average weight vector And the fuzzy comprehensive evaluation matrix R = (rnj ) M×m The preferred selection matrix Q was obtained through calculation. n(w) The formula is as follows:

[0034]

[0035] According to the preference selection matrix Q n(w) Determine the weight value w for each target charging station. n .

[0036] Preferably, the first charging piles are classified according to charging demand to obtain a first classification result, including:

[0037] Each first charging pile is analyzed to obtain its charging power information.

[0038] If the charging power information of each first charging pile matches the charging needs of the target vehicle, all first charging piles are classified as one type of charging pile.

[0039] If none of them match, then all first-class charging piles are classified as second-class charging piles.

[0040] Otherwise, determine that all first-class charging piles include both Class I and Class II charging piles.

[0041] Preferably, when only one type of charging pile exists in the first classification result, the optimal charging pile is selected from the first charging pile, including:

[0042] Obtain the coordinates of all first charging piles in a class of charging piles, and the first distance M from the parking lot entrance to each first charging pile. i and the second distance N from the parking lot exit to each first charging station i ;

[0043] Determine the total distance from the same first charging pile to the parking lot entrance and exit;

[0044] From the sum of all distances corresponding to the aforementioned type of charging pile, select the shortest total distance (M). i +N i ) min The matched charging pile is determined as the optimal charging pile;

[0045] When a type of charging pile contains only one charging pile, the corresponding charging pile is determined to be the optimal charging pile.

[0046] Preferably, when there are two types of charging piles in the first classification result, candidate charging piles in each type of charging pile are obtained, and the optimal charging pile is selected from them, including:

[0047] The second category of charging piles in the first classification results is identified as the first candidate charging piles;

[0048] The remaining charging piles in the target charging pile set, excluding the first charging pile, are identified as the second charging piles;

[0049] From the second set of charging piles, select the charging piles that meet the charging needs of the target vehicle and determine them as the second candidate charging piles.

[0050] The second candidate charging piles are sorted from low to high according to their historical usage rate to obtain the first list;

[0051] The second list is obtained by sorting the target vehicles from the parking lot entrance to each second candidate charging station in ascending order;

[0052] The first list and the second list are weighted averaged with the same number of charging stations to obtain the key list;

[0053] Extract the third candidate charging pile from the key list that meets the preset criteria;

[0054] The first and third candidate charging piles are analyzed, and the optimal charging pile is selected to achieve effective charging.

[0055] Preferably, the first and third candidate charging piles are analyzed, and the optimal charging pile is selected to achieve effective charging, including:

[0056] The path corresponding to the minimum time for the target vehicle to reach each first candidate charging pile from the parking lot entrance is planned to obtain the minimum time set for the target vehicle to reach each first candidate charging pile.

[0057] Extract the minimum value from the minimum time set and determine it as the first candidate time;

[0058] The first candidate charging pile corresponding to the first candidate time is determined as the first candidate charging pile;

[0059] The arrival time and queuing time of the target vehicle at each of the third candidate charging stations are obtained, and then added together to obtain the second candidate time set.

[0060] The second candidate charging pile corresponding to the smallest time in the second set of candidate times is determined as the second candidate charging pile;

[0061] If the first candidate time is not less than the second candidate time, the second candidate charging pile is determined to be the optimal charging pile.

[0062] Otherwise, the first candidate charging station is determined as the optimal charging station, and charging is initiated.

[0063] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0064] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0065] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0066] Figure 1 This is a flowchart of a vehicle charging planning method for a parking lot according to an embodiment of the present invention. Detailed Implementation

[0067] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0068] This invention provides a vehicle charging planning method for parking lots, such as... Figure 1 As shown, it includes:

[0069] Step 1: Receive the target vehicle's location information, remaining battery power, and data information to determine the target vehicle's range and charging requirements;

[0070] Step 2: Collect the attribute information of the target parking lot and combine it with the range information of the target vehicle to select the first charging pile from the charging piles in the target parking lot.

[0071] Step 3: Classify the first charging piles according to charging demand to obtain the first classification result;

[0072] Step 4: When there is only one type of charging pile in the first classification result, select the optimal charging pile from the first charging pile;

[0073] Step 5: When there are two types of charging piles in the first classification result, obtain the candidate charging piles in each type of charging pile, and select the optimal charging pile from them.

[0074] In this embodiment, the location information of the target vehicle refers to the current latitude and longitude coordinates of the target vehicle and the path length from the target parking lot; the remaining power actually refers to the current remaining power percentage; the data information includes the vehicle's average driving speed, power consumption rate, preset minimum reserve power, etc.; the target vehicle's range information is calculated by combining the target vehicle's remaining power percentage, power consumption rate, and driving speed; the charging demand refers to the target vehicle's charging power information, charging demand time, current state of charge information, and expected state of charge information after charging is completed.

[0075] In this embodiment, the attribute information of the target parking lot includes the location coordinates, area size, internal path layout, total number of charging piles, and charging pile layout of the target parking lot.

[0076] In this embodiment, the first charging pile refers to an idle charging pile that the target vehicle can reach by driving from the parking lot entrance.

[0077] In this embodiment, the first classification result refers to the result of classifying charging piles based on the charging needs of the target vehicle. Its purpose is mainly to lay the foundation for quickly matching the most suitable charging pile for the target vehicle and meet the user's needs.

[0078] In this embodiment, one type of charging pile refers to the first charging pile that matches the charging needs of the target vehicle; the optimal charging pile refers to the idle charging pile that best meets the charging needs of the target vehicle based on the real-time data of the target vehicle, where the real-time data refers to the target vehicle's current remaining power, current location coordinates, and power consumption rate; the two types of charging piles refer to the first charging pile that does not fully meet the charging needs of the target vehicle and the charging piles among the target charging piles that are not idle.

[0079] The beneficial effects of the above technical solution are: by effectively predicting the real-time changes in the charging pile status in the target parking lot accessible to the vehicle based on the charging needs of the target vehicle and the attribute information of the target parking lot, the optimal charging pile with the most reasonable match can be selected, which not only meets the charging needs of the target vehicle, but also improves the utilization rate of the charging pile.

[0080] This invention provides a vehicle charging planning method for parking lots, which involves collecting attribute information of the target parking lot and combining it with the target vehicle's range information to select a first charging pile from the charging piles in the target parking lot, including:

[0081] Obtain the target parking lot attribute information;

[0082] Retrieve the location information from the target parking lot's attribute information, and based on the target vehicle's location information, average driving speed, and target vehicle's remaining range information, determine the vehicle's arrival time at the target parking lot and its real-time remaining battery power upon arrival.

[0083] Subtract the preset minimum reserve power from the real-time remaining power to obtain the first real-time power.

[0084] The first driving range is obtained based on the first real-time battery level, the average vehicle speed, and the vehicle's power consumption rate.

[0085] Identify all charging stations in the parking area that correspond to the first driving range, and construct a target charging station set;

[0086] Based on the parking and charging demand intensity in the target parking lot attribute information and the current time when the target vehicle arrives at the target parking lot, predict all idle charging piles in the target charging pile set when the vehicle arrives at the parking lot, and select the first charging pile.

[0087] In this embodiment, the location information in the target parking lot attribute information refers to the latitude and longitude coordinates of the target parking lot.

[0088] In this embodiment, the first real-time power is the power obtained by subtracting the preset minimum reserve power from the real-time remaining power of the target vehicle when it arrives at the parking lot entrance; the preset minimum reserve power is set in advance, and its purpose is to reduce battery wear on the target vehicle and extend battery life, and to prevent the target vehicle from being unable to move in the event of an emergency; the vehicle wear rate refers to the power consumption information of the target vehicle per unit mileage.

[0089] In this embodiment, the first driving range refers to the corresponding parking area centered on the parking lot entrance, based on the first real-time battery level, the average driving speed of the vehicle, and the vehicle's power consumption rate. Its main purpose is to filter the charging pile locations that the target vehicle can reach, obtain the target charging pile set, and lay the foundation for selecting the optimal charging pile in the future. The target charging pile set consists of all the charging piles that the target vehicle can reach from the parking lot entrance.

[0090] In this embodiment, the parking charging demand intensity includes the historical parking charging traffic flow and historical parking charging data of the target parking lot; wherein, the historical parking charging data is related to the historical parking charging time and the historical usage of each charging pile.

[0091] In this embodiment, the first charging pile refers to the target charging pile that is in an idle state.

[0092] The beneficial effects of the above technical solution are as follows: by obtaining the first real-time battery level and average driving speed of the target vehicle when it arrives at the entrance of the target parking lot, the first driving range of the target vehicle is obtained, and then the target charging piles in the parking lot area corresponding to the first driving range are obtained; by predicting the target charging piles, the idle target charging piles, i.e. the first charging piles, can be obtained, which can effectively improve the screening speed of charging piles in the target parking lot and provide a basis for selecting the optimal charging pile for the target vehicle.

[0093] This invention provides a vehicle charging planning method for parking lots, which predicts all available charging stations in a target charging station set when a vehicle arrives at the parking lot, including:

[0094] Step 01: Determine the total number M of target charging stations in the target charging station set. Simultaneously, number all target charging stations and obtain the weight value w for each target charging station. n where n∈1, 2, 3, ..., M;

[0095] Step 02: Train a prediction model based on the historical parking and charging data of the target parking lot, wherein the historical parking and charging data is related to the historical parking and charging time and the historical usage of each charging pile;

[0096] Step 03: Input the target charging pile status information of the previous moment and the current time when the vehicle arrives at the target parking lot into the prediction model, and predict the status value of each charging pile, as shown in the following formula:

[0097]

[0098] Where t represents the current time when the target vehicle arrives at the parking lot; x n(t) This represents the historical state periodic information of the nth charging pile at the same time t; K n This indicates the predicted state information of the nth charging pile at the previous moment. The error coefficient is represented as the calculated value, and its range is (0, e). -2 );w n This represents the weight value of the nth charging pile, with a value range of (0, 1, n∈1, 2, 3, ..., M). This represents the predicted state value of the nth charging pile;

[0099] The predicted state value is judged based on the preset standard value;

[0100] When the predicted state value is not greater than the preset standard value, the corresponding target charging pile is determined to be an idle charging pile.

[0101] In this embodiment, the historical parking and charging data is related to the historical parking and charging time and the historical usage of each charging pile, and its purpose is to train the prediction model; the historical state cycle information refers to the real-time state change pattern of the charging pile.

[0102] In this embodiment, the preset standard value is set in advance, typically 0.35.

[0103] In this embodiment, for example, there are target charging piles 1, 2, and 3, with corresponding predicted state values ​​of 0.2, 0.3, and 0.5, respectively. Based on the preset standard value of 0.35, charging pile 1 and charging pile 2 are determined to be idle charging piles.

[0104] The beneficial effects of the above technical solution are: by using historical parking and charging data of the target parking lot to train the prediction model; by using the target charging pile status information of the previous moment and the current moment when the vehicle arrives at the target parking lot as input quantities into the prediction model, and combining the obtained weight value of each target charging pile, the predicted status value of each target charging pile can be obtained; based on the preset standard value, idle target charging piles can be effectively obtained.

[0105] This invention provides a vehicle charging planning method for parking lots, which obtains the weight value w of each target charging pile. n ,include:

[0106] Step 11: Construct a fuzzy factor set A = (a1, a2, ... a m ), where a1 represents the first factor influencing driver preference; a2 represents the second factor influencing driver preference; a m This represents the m-th factor influencing driver preference;

[0107] Step 12: Create evaluation matrix B, where (b n1 ,b n2 ,…,b nm ) represents the evaluation vector of the nth charging pile, where n ranges from [1, M]; b nj Represents the evaluation vector (b) n1 ,b n2 ,…,b nm The value of the j-th factor influencing driver preference in (), where j ranges from [1, m];

[0108] Step 13: Normalize the evaluation matrix B to define the fuzzy comprehensive evaluation matrix R = (r nj ) M×m , where r nj This represents the fuzzy evaluation of the j-th factor for the n-th charging pile;

[0109] Step 14: Define the weights of the charging feedback collected from several drivers with different driving experiences to obtain a feedback weight matrix;

[0110] Step 15: After removing the maximum and minimum weight values ​​from each column of the feedback weight matrix, calculate the average of the remaining weights in the corresponding column to obtain the average weight vector.

[0111] Step 16: Combine the average weight vector And the fuzzy comprehensive evaluation matrix R = (r nj ) M×m The preferred selection matrix Q was obtained through calculation. n(w) The formula is as follows:

[0112]

[0113] According to the preference selection matrix Q n(w) Determine the weight value w for each target charging station. n .

[0114] In this embodiment, the fuzzy factor set consists of factors that influence driver preferences, that is, factors that influence the driver's choice of charging stations, such as the distance between the target vehicle and the charging station, the status of the path to the charging station, the status of the charging station, the remaining battery power, etc. The fuzzy concept is introduced to quantify the influencing factors for easier analysis. The evaluation matrix is ​​a tool for analyzing the factors that influence driver preferences, mainly for assigning values ​​to the factors that influence driver preferences.

[0115] In this embodiment, the fuzzy comprehensive evaluation matrix is ​​obtained by normalizing the evaluation matrix. The normalization process is to eliminate the influence of different units during the calculation process. For example, the calculation units for the distance between the target vehicle and the charging pile and the remaining power are different, and the numerical characteristics are quite different. In this case, normalization is required.

[0116] In this embodiment, charging feedback refers to the factors that influence the selection of charging stations by drivers of different genders, ages, and driving experiences; the feedback weight matrix is ​​obtained by weight analysis based on the charging feedback.

[0117] In this embodiment, the average weight vector The weights are obtained by averaging the values ​​after removing the maximum and minimum weights from each column of the weight matrix. The purpose is to make the feedback weight matrix more representative and improve its accuracy.

[0118] In this embodiment, the preferred selection matrix contains the weight value of each target charging pile, and the preference order of each target charging pile can be sorted according to the preferred selection matrix.

[0119] The beneficial effects of the above technical solution are as follows: by analyzing the factors that influence drivers' choice of charging piles, a fuzzy comprehensive evaluation matrix is ​​obtained; by performing weight analysis on the influencing factors of different drivers' choice of charging piles, an average weight vector is obtained; and by combining the fuzzy comprehensive evaluation matrix and the average weight vector to obtain the optimal selection matrix, the weight value of each charging pile can be obtained, providing effective data for determining whether a charging pile is idle.

[0120] This invention provides a vehicle charging planning method for parking lots, which classifies the first charging piles according to charging demand to obtain a first classification result, including:

[0121] Each first charging pile is analyzed to obtain its charging power information.

[0122] If the charging power information of each first charging pile matches the charging needs of the target vehicle, all first charging piles are classified as one type of charging pile.

[0123] If none of them match, then all first-class charging piles are classified as second-class charging piles.

[0124] Otherwise, determine that all first-class charging piles include both Class I and Class II charging piles.

[0125] In this embodiment, the charging power information includes the charging rate, charging voltage, and charging time.

[0126] In this embodiment, for example, there are first charging piles 1, 2, and 3, where charging pile 1 and charging pile 2 are fast charging piles and charging pile 3 is a slow charging pile; it is determined that the charging demand of the target vehicle is fast charging, therefore, the first charging piles 1 and 2 are classified as Class I charging piles and the first charging pile 3 is classified as Class II charging piles.

[0127] The beneficial effects of the above technical solution are: by classifying the charging power information of the first charging pile based on the charging needs of the target vehicle, the rationality of matching charging piles is effectively improved, laying the foundation for determining the optimal charging pile in the future.

[0128] This invention provides a vehicle charging planning method for parking lots. When only one type of charging pile exists in the first classification result, the optimal charging pile is selected from the first charging pile, including:

[0129] Obtain the coordinates of all first charging piles in a class of charging piles, and the first distance M from the parking lot entrance to each first charging pile. i and the second distance N from the parking lot exit to each first charging station i ;

[0130] Determine the total distance from the same first charging pile to the parking lot entrance and exit;

[0131] From the sum of all distances corresponding to the aforementioned type of charging pile, select the shortest total distance (M). i +N i ) min The matched charging pile is determined as the optimal charging pile;

[0132] When a type of charging pile contains only one charging pile, the corresponding charging pile is determined to be the optimal charging pile.

[0133] In this embodiment, for example, there are first charging piles 1, 2, and 3 in a class of charging piles, and the total distances from the parking lot entrance and exit are (M1+1), (M2+2), and (M3+3), respectively, and (M1+1)>(M2+2)>(M3+3); at this time, the first charging pile 3 is determined to be the optimal charging pile.

[0134] The beneficial effects of the above technical solution are: by using the location coordinates of a type of charging pile, the distance from each charging pile to the entrance and exit of the target parking lot can be obtained; the charging pile corresponding to the minimum distance can be determined as the optimal charging pile for charging to save time entering and exiting the parking lot; when there is only one type of charging pile, it can be determined that the type of charging pile is the optimal charging pile.

[0135] This invention provides a vehicle charging planning method for parking lots. When there are two types of charging piles in the first classification result, candidate charging piles in each type of charging pile are obtained, and the optimal charging pile is selected from them, including:

[0136] The second category of charging piles in the first classification results is identified as the first candidate charging piles;

[0137] The remaining charging piles in the target charging pile set, excluding the first charging pile, are identified as the second charging piles;

[0138] From the second set of charging piles, select the charging piles that meet the charging needs of the target vehicle and determine them as the second candidate charging piles.

[0139] The second candidate charging piles are sorted from low to high according to their historical usage rate to obtain the first list;

[0140] The second list is obtained by sorting the target vehicles from the parking lot entrance to each second candidate charging station in ascending order;

[0141] The first list and the second list are weighted averaged with the same number of charging stations to obtain the key list;

[0142] Extract the third candidate charging pile from the key list that meets the preset criteria;

[0143] The first and third candidate charging piles are analyzed, and the optimal charging pile is selected to achieve effective charging.

[0144] In this embodiment, the first candidate charging pile refers to a Class II charging pile, which is a first charging pile that does not completely match the charging needs of the target vehicle.

[0145] In this embodiment, the second charging pile refers to a charging pile in the target charging pile set that is not idle; the second candidate charging pile refers to a second charging pile that meets the charging needs of the target vehicle.

[0146] In this embodiment, the weighted average is mainly used to predict the future state trend of the second charging pile.

[0147] In this embodiment, the key list is constructed based on the key values ​​obtained by weighted averaging of the first list and the second list and the corresponding order of the charging piles; the preset standard is set in advance, which means that the key value corresponding to the charging pile is not greater than 0.3; the third candidate charging pile refers to the second candidate charging pile that meets the preset standard.

[0148] In this embodiment, for example, if there is a second candidate charging pile 1 in the key list, corresponding to a key value of 0.3, then it is determined that the second candidate charging pile meets the preset standard, which is the third candidate charging pile.

[0149] The beneficial effects of the above technical solution are as follows: by weighting the non-idle charging piles in the target charging pile set according to their historical usage rate and distance to the parking lot entrance, the candidate charging piles can be effectively screened out. Then, by combining the analysis of the first charging pile that does not fully meet the charging needs of the target vehicle, the optimal matching charging pile can be quickly found when there is no idle charging pile that fully meets the charging needs of the target vehicle within the first driving range.

[0150] This invention provides a vehicle charging planning method for parking lots, which analyzes a first candidate charging pile and a third candidate charging pile, and selects the optimal charging pile to achieve effective charging, including:

[0151] The path corresponding to the minimum time for the target vehicle to reach each first candidate charging pile from the parking lot entrance is planned to obtain the minimum time set for the target vehicle to reach each first candidate charging pile.

[0152] Extract the minimum value from the minimum time set and determine it as the first candidate time;

[0153] The first candidate charging pile corresponding to the first candidate time is determined as the first candidate charging pile;

[0154] The arrival time and queuing time of the target vehicle at each of the third candidate charging stations are obtained, and then added together to obtain the second candidate time set.

[0155] The second candidate charging pile corresponding to the smallest time in the second set of candidate times is determined as the second candidate charging pile;

[0156] If the first candidate time is not less than the second candidate time, the second candidate charging pile is determined to be the optimal charging pile.

[0157] Otherwise, the first candidate charging station is determined as the optimal charging station, and charging is initiated.

[0158] In this embodiment, for example, there exists a minimum time set T. i The set includes T1, T2, and T3, which correspond to the first candidate charging piles 1, 2, and 3. Since T1 > T2 > T3, T3 is the minimum value in the latest time set. At this time, the first candidate charging pile corresponding to T3 is determined as the first candidate charging pile, and T3 is the first candidate time.

[0159] In this embodiment, queuing time refers to the time required for the target vehicle to wait for the previous vehicle to leave before arriving at each of the third candidate charging stations; the second candidate time set is actually the sum of the path time of the target vehicle to each of the third candidate charging stations and the corresponding queuing time required after arrival.

[0160] In this embodiment, for example, there exists a minimum value t in the second candidate time set. a Determine t a The corresponding third candidate charging station is the second candidate charging station, t a This is the second candidate time.

[0161] The beneficial effects of the above technical solution are: by obtaining the minimum time required for the target vehicle to reach the first and third candidate charging piles and achieve charging, the optimal charging pile can be selected from them. This can quickly and reasonably match the target vehicle with a charging pile to achieve charging while saving time, and meet the charging needs as much as possible.

[0162] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A vehicle charging planning method for parking lots, characterized in that, include: Step 1: Receive the target vehicle's location information, remaining battery power, and data information to determine the target vehicle's range and charging requirements; Step 2: Collect the attribute information of the target parking lot and combine it with the range information of the target vehicle to select the first charging pile from the charging piles in the target parking lot. Step 3: Classify the first charging piles according to charging demand to obtain the first classification result; Step 4: When there is only one type of charging pile in the first classification result, select the optimal charging pile from the first charging pile; Step 5: When there are two types of charging piles in the first classification result, obtain the candidate charging piles in each type of charging pile, and select the optimal charging pile from them; Collect attribute information of the target parking lot and combine it with the target vehicle's range information to select the first charging station from the charging stations in the target parking lot, including: Obtain the target parking lot attribute information; Retrieve the location information from the target parking lot's attribute information, and based on the target vehicle's location information, average driving speed, and target vehicle's remaining range information, determine the vehicle's arrival time at the target parking lot and its real-time remaining battery power upon arrival. Subtract the preset minimum reserve power from the real-time remaining power to obtain the first real-time power. The first driving range is obtained based on the first real-time battery level, the average vehicle speed, and the vehicle power consumption rate. Identify all charging stations in the parking area that correspond to the first driving range, and construct a target charging station set; Based on the parking and charging demand intensity in the target parking lot attribute information and the current time when the target vehicle arrives at the target parking lot, predict all idle charging piles in the target charging pile set when the vehicle arrives at the parking lot, and select the first charging pile. Predict all available charging stations in the target charging station set when the vehicle arrives at the parking lot, including: Step 01: Determine the total number M of target charging stations in the target charging station set. Simultaneously, number all target charging stations and obtain the weight value for each target charging station. , where n ; Step 02: Train a prediction model based on the historical parking and charging data of the target parking lot, wherein the historical parking and charging data is related to the historical parking and charging time and the historical usage of each charging pile; Step 03: Input the target charging pile status information of the previous moment and the current time when the vehicle arrives at the target parking lot into the prediction model, and predict the status value of each charging pile, as shown in the following formula: in, Indicates the current time when the target vehicle arrives at the parking lot; This represents the historical state cycle information of the nth charging pile at the same time t. This indicates the predicted state information of the nth charging pile at the previous moment. The error coefficient is represented by the formula, and its value range is [value missing]. ; This represents the weight value of the nth charging pile, with a value range of... n ; This represents the predicted state value of the nth charging pile; The predicted state value is judged based on the preset standard value; When the predicted state value is not greater than the preset standard value, the corresponding target charging pile is determined to be an idle charging pile; Obtain the weight value of each target charging station. ,include: Step 11: Construct a fuzzy factor set ,in, This indicates the first factor influencing driver preference; This indicates the second factor influencing driver preference; This represents the m-th factor influencing driver preference; Step 12: Create evaluation matrix B, where, Let n be the evaluation vector for the nth charging pile, where n takes values ​​ranging from 1 to 2. Represents the evaluation vector The value of the j-th factor influencing driver preference, where j ranges from 1 to 1. ; Step 13: Normalize the evaluation matrix B to define the fuzzy comprehensive evaluation matrix. ,in, This represents the fuzzy evaluation of the j-th factor for the n-th charging pile; Step 14: Define the weights of the charging feedback collected from several drivers with different driving experiences to obtain the feedback weight matrix; Step 15: After removing the maximum and minimum weight values ​​from each column of the feedback weight matrix, calculate the average of the remaining weights in the corresponding column to obtain the average weight vector. ; Step 16: Combine the average weight vector And fuzzy comprehensive evaluation matrix R The preferred selection matrix was obtained through calculation. The formula is as follows: According to the preference selection matrix Determine the weight value of each target charging station. ; Historical state cycle information refers to the real-time state change pattern of charging piles.

2. The vehicle charging planning method for parking lots as described in claim 1, characterized in that, Based on charging demand, the first charging pile is classified to obtain the first classification result, including: Each first charging pile is analyzed to obtain its charging power information. If the charging power information of each first charging pile matches the charging needs of the target vehicle, all first charging piles are classified as one type of charging pile. If none of them match, then all first-class charging piles are classified as second-class charging piles. Otherwise, determine that all first-class charging piles include both Class I and Class II charging piles.

3. The vehicle charging planning method for parking lots as described in claim 1, characterized in that, When only one type of charging pile exists in the first classification result, the optimal charging pile is selected from the first charging pile, including: Obtain the coordinates of all first charging piles in a class of charging piles, and the first distance from the parking lot entrance to each first charging pile. and the second distance from the parking lot exit to each first charging station ; Determine the total distance from the same first charging pile to the parking lot entrance and exit; Select the shortest total distance from all total distances corresponding to the aforementioned type of charging piles. The matched charging pile is determined as the optimal charging pile; When a type of charging pile contains only one charging pile, the corresponding charging pile is determined to be the optimal charging pile.

4. The vehicle charging planning method for parking lots as described in claim 1, characterized in that, When there are two types of charging piles in the first classification result, the candidate charging piles in each type are obtained, and the optimal charging pile is selected from them, including: The second category of charging piles in the first classification results is identified as the first candidate charging piles; The remaining charging piles in the target charging pile set, excluding the first charging pile, are identified as the second charging piles; From the second set of charging piles, select the charging piles that meet the charging needs of the target vehicle and determine them as the second candidate charging piles. The second candidate charging piles are sorted from low to high according to their historical usage rate to obtain the first list; The second list is obtained by sorting the target vehicles from the parking lot entrance to each second candidate charging station in ascending order; The first list and the second list are weighted averaged with the same number of charging stations to obtain the key list; Extract the third candidate charging pile from the key list that meets the preset criteria; The first and third candidate charging piles are analyzed, and the optimal charging pile is selected to achieve effective charging.

5. The vehicle charging planning method for parking lots as described in claim 4, characterized in that, The first and third candidate charging piles are analyzed, and the optimal charging pile is selected to achieve effective charging, including: The path corresponding to the minimum time for the target vehicle to reach each first candidate charging pile from the parking lot entrance is planned to obtain the minimum time set for the target vehicle to reach each first candidate charging pile. Extract the minimum value from the minimum time set and determine it as the first candidate time; The first candidate charging pile corresponding to the first candidate time is determined as the first candidate charging pile; The arrival time and queuing time of the target vehicle at each of the third candidate charging stations are obtained, and then added together to obtain the second candidate time set. The second candidate charging pile corresponding to the smallest time in the second set of candidate times is determined as the second candidate charging pile; If the first candidate time is not less than the second candidate time, the second candidate charging pile is determined to be the optimal charging pile. Otherwise, the first candidate charging station is determined as the optimal charging station, and charging is initiated.

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