Mileage dimension vehicle maintenance dynamic recommendation method and system based on driving behaviors

Abstract

The invention relates to the technical field of vehicle maintenance, and discloses a mileage dimension vehicle maintenance dynamic recommendation method and system based on driving behaviors, and the method comprises the steps: obtaining a vehicle brand model, an initial mileage and a preset maintenance mileage inputted by a user; querying a vehicle model database based on the vehicle brand model, and obtaining a standard maintenance item table and a brand load feature matrix; calculating a driving wear index according to the brand load feature matrix; calculating a dynamic compensation mileage threshold value of each maintenance item according to the driving wear index; comparing the difference value between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold value to generate a recommended maintenance item list; and calculating the cost of each maintenance item and the total cost according to the recommended maintenance item list. According to the scheme, precision and individuation of vehicle maintenance can be realized.

Description

Technical Field

[0001] The present invention belongs to the field of vehicle maintenance technology, and in particular relates to a method and system for dynamically recommending vehicle maintenance in the mileage dimension based on driving behavior. Background Art

[0002] Vehicle maintenance technology, a core area of ​​the automotive aftermarket, has a direct impact on road safety and resource efficiency. With the increasing intelligence of vehicles and the escalating demand for user services, the traditional maintenance model that relies on manual experience and fixed cycles can no longer meet the requirements for precision and transparency.

[0003] Current vehicle maintenance technology primarily relies on manufacturers' fixed-cycle recommendations and maintenance personnel's experience, lacking a quantitative assessment of actual driving conditions and vehicle load status. Traditional solutions typically use static thresholds to trigger maintenance reminders, failing to recognize the accelerated wear of mechanical components caused by abnormal operating conditions such as high-speed driving and frequent heavy loading. This can easily lead to the failure of key components before their theoretical lifespan or premature replacement, resulting in wasteful resources. Existing digital systems are mostly limited to basic information recording and simple mileage reminders. They lack a dynamic correlation model between driving behavior data and maintenance strategies, making accurate predictions difficult. Furthermore, the service model is characterized by a single model, lacking flexible solutions adapted to different user scenarios, and a pricing system with information black boxes, making it difficult for car owners to verify the necessity and cost rationality of maintenance items. These shortcomings have led to high vehicle maintenance costs, inconsistent maintenance results, and difficulties in improving user trust.

[0004] Therefore, there is an urgent need to develop a dynamic recommendation method and system for vehicle maintenance based on mileage dimension of driving behavior, which can realize the precision and personalization of vehicle maintenance. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a dynamic recommendation method and system for vehicle maintenance in the mileage dimension based on driving behavior, which can achieve precise and personalized vehicle maintenance.

[0006] The present invention provides a method for dynamically recommending vehicle maintenance based on mileage and driving behavior, the method comprising the following steps:

[0007] S1. Obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user;

[0008] S2. Query the vehicle model database based on the vehicle brand and model to obtain a standard maintenance item table and a brand load characteristic matrix;

[0009] S3. Calculate the driving wear index based on the brand load characteristic matrix;

[0010] S4. Calculating a dynamic compensation mileage threshold for each maintenance item based on the driving wear index;

[0011] S5. Compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items;

[0012] S6. Calculate the cost of each maintenance item and the total cost based on the recommended maintenance item list.

[0013] Furthermore, in S2, based on the vehicle brand and model, the vehicle model database is queried to obtain a table of standard maintenance items including:

[0014] Query the vehicle model database based on the vehicle brand and model to obtain all maintenance items for the target vehicle model;

[0015] Obtain the benchmark mileage corresponding to the maintenance items, the life coefficient of each accessory, and the cost price of each accessory to build a maintenance item table.

[0016] Furthermore, the calculation formula for the life coefficient of each accessory is as follows:

[0017]

[0018] Among them, q k Indicates the life coefficient of the accessory corresponding to the kth maintenance item, represents the base mileage corresponding to the kth maintenance item, It represents the average maintenance mileage of the accessories corresponding to the k-th maintenance item.

[0019] Furthermore, in S2, the vehicle model database is queried based on the vehicle brand and model to obtain the brand load feature matrix including:

[0020] Query the vehicle model database according to the vehicle brand and model to obtain the speed ratio coefficient and load factor of the target vehicle model;

[0021] Construct the brand load characteristic matrix based on the speed ratio coefficient and load coefficient.

[0022] Furthermore, the calculation method of the speed ratio coefficient and the load factor is as follows:

[0023]

[0024] Among them, α represents the speed ratio coefficient, R avg represents the historical average speed of the target vehicle model, R econ Indicates the middle value of the economic speed range of the target vehicle model;

[0025]

[0026] Where β represents the load factor, W median Represents the median load distribution of the target vehicle type, W maxIndicates the maximum design load of the target vehicle type.

[0027] Furthermore, in S3, the formula for calculating the driving wear index based on the brand load characteristic matrix is ​​as follows:

[0028] Δm=m p -m0;

[0029]

[0030] Where W represents the driving wear index, Δm represents the difference between the preset maintenance mileage and the initial mileage, and m p represents the preset maintenance mileage, m0 represents the initial mileage, α represents the speed ratio coefficient, β represents the load coefficient, D1 represents the speed item wear increment coefficient, and D2 represents the load item wear increment coefficient.

[0031] Furthermore, in S4, the calculation formula for calculating the dynamic compensation mileage threshold of each maintenance item based on the driving wear index is as follows:

[0032]

[0033] in, represents the mileage threshold after dynamic compensation of the kth maintenance item, Indicates the baseline mileage of the kth maintenance item.

[0034] Furthermore, in S5, the difference between the preset maintenance mileage and the initial mileage is compared with the dynamic compensation mileage threshold to generate a list of recommended maintenance items including:

[0035]

[0036] Among them, N k represents the maintenance coefficient of the kth maintenance item, q k Indicates the life coefficient of the accessory corresponding to the kth maintenance item;

[0037] Export the maintenance items with a maintenance factor of 1 and generate a list of recommended maintenance items.

[0038] Furthermore, in S6, the cost of each maintenance item and the total cost are calculated based on the recommended maintenance item list, including:

[0039] Determine the cost of each maintenance item based on the recommended maintenance item list and the cost price of each accessory corresponding to each maintenance item;

[0040] The total cost is obtained by summing the costs of each maintenance item in the recommended maintenance item list.

[0041] The present invention also provides a mileage-based dynamic vehicle maintenance recommendation system for driving behavior, which is used to implement the above-mentioned mileage-based dynamic vehicle maintenance recommendation method. The system is characterized in that it includes the following modules:

[0042] The data acquisition module is used to obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user;

[0043] The matching module is used to query the vehicle model database based on the vehicle brand and model to obtain the standard maintenance item table and brand load characteristic matrix;

[0044] A calculation module, configured to calculate a driving wear index based on a brand load characteristic matrix; and to calculate a dynamic compensation mileage threshold for each maintenance item based on the driving wear index;

[0045] The maintenance item recommendation module is used to compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items;

[0046] The maintenance cost calculation module is used to calculate the cost of each maintenance item and the total cost based on the recommended maintenance item list.

[0047] The embodiments of the present invention have the following technical effects:

[0048] The present invention automatically adapts to corresponding maintenance services based on the vehicle model robustness matching mechanism, saving employees' analysis time costs. Through a nonlinear mileage compensation algorithm and the calculation of the driving wear index driven by brand characteristics, and by analyzing the coupling effect of the speed ratio coefficient and the load coefficient, the recommended cycle of each maintenance item is dynamically adjusted to avoid excessive or insufficient maintenance caused by traditional fixed-cycle maintenance. The actual working conditions of the vehicle are combined with the manufacturer's recommended standards through a standardized service system, thus achieving precise and personalized vehicle maintenance. The vehicle model database integrates accessories and maintenance service quotations, visualizes the maintenance item decision-making process, reduces service costs, and improves the decision-making flexibility of car owners, ultimately forming an intelligent maintenance decision-making support capability in the dimension of the entire life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 This is a flowchart of a method for dynamically recommending vehicle maintenance based on mileage dimension of driving behavior provided by an embodiment of the present invention;

[0051] Figure 2 This is a logic diagram of a mileage-based vehicle maintenance dynamic recommendation method based on driving behavior provided by an embodiment of the present invention;

[0052] Figure 3 This is a flow chart of a daily running system obtaining the cost price of each accessory provided by an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of a daily running system service interface provided by an embodiment of the present invention;

[0054] Figure 5 This is a schematic diagram of a product quotation page interface of a daily running system provided by an embodiment of the present invention;

[0055] Figure 6 This is a schematic diagram of a purchased service interface of a daily running system provided by an embodiment of the present invention;

[0056] Figure 7 3 is a schematic diagram of the structure of a mileage-based vehicle maintenance dynamic recommendation system based on driving behavior provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0058] The embodiment of the present invention provides a method for dynamically recommending vehicle maintenance based on the mileage dimension of driving behavior, which is implemented based on the dynamic vehicle maintenance recommendation system based on the mileage dimension of driving behavior provided by this application, namely the "Daily Run" system. The "Daily Run" system is a vehicle maintenance service system that integrates backend operations and front-end applications in an integrated algorithm logic and application model. After the car owner provides the brand and model information of the vehicle and the mileage information of the vehicle, the system will recommend corresponding maintenance items and maintenance plans to the car owner according to the preset algorithm logic in combination with the mileage of the vehicle expected to receive services in the future. For car owners who lack car maintenance experience but use their cars frequently, this service system effectively guides the car owners on when to maintain what items; at the same time, due to the standardization and batching of the packages, the service costs of the service team are reduced, and the car owners intuitively feel the price benefits and the improvement in service quality.

[0059] Figure 1 This is a flowchart of a method for dynamically recommending vehicle maintenance based on mileage dimension of driving behavior provided by an embodiment of the present invention. Figure 2This is a logic diagram of a mileage-based vehicle maintenance dynamic recommendation method based on driving behavior provided by an embodiment of the present invention. Figure 1 and Figure 2 , the method comprises the following steps:

[0060] S1. Obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user.

[0061] Figure 4 This is a schematic diagram of a daily running system service interface provided by an embodiment of the present invention. Figure 5 This is a schematic diagram of a product quotation page interface of a daily running system provided by an embodiment of the present invention, see Figure 4 and Figure 5 When users access the "Daily Run" app's service interface, they are prompted to enter their vehicle's make and model, initial mileage, and target maintenance mileage. This information can be entered via a drop-down menu or text input. Initial mileage is manually entered by the user, using the current vehicle's mileage. Maintenance mileage can be set by dragging a virtual vehicle icon within the interface or manually entering the target mileage.

[0062] S2. Query the vehicle model database based on the vehicle brand and model to obtain a standard maintenance item table and a brand load characteristic matrix.

[0063] In some embodiments, querying a vehicle model database based on the vehicle brand and model to obtain a list of standard maintenance items includes:

[0064] Query the vehicle model database based on the vehicle brand and model to obtain all maintenance items for the target vehicle model;

[0065] Obtain the benchmark mileage corresponding to the maintenance items, the life coefficient of each accessory, and the cost price of each accessory to build a maintenance item table.

[0066] The benchmark mileage corresponding to the maintenance items can be extracted from the target vehicle model's maintenance manual or the original equipment manufacturer's database to obtain the official recommended cycle for each maintenance item. For example, the benchmark mileage for oil change of Toyota Camry = 10,000 kilometers.

[0067] The calculation formula for the life coefficient of each accessory is as follows:

[0068]

[0069] Among them, q k Indicates the life coefficient of the accessories corresponding to the kth maintenance item of the target vehicle model, represents the benchmark mileage corresponding to the kth maintenance item of the target vehicle model, Represents the average maintenance mileage for the parts corresponding to the kth maintenance item on the target vehicle. This coefficient serves as the basis for dynamic threshold adjustment, ensuring that maintenance recommendations meet both manufacturer standards and actual operating conditions.

[0070] in, Figure 3 This is a flowchart of a daily running system for obtaining the cost price of each accessory provided by an embodiment of the present invention, see Figure 3 , get the cost price of each accessory including:

[0071] According to the target vehicle model, the corresponding accessories for each maintenance item are analyzed to determine whether they are branded parts or original parts, and the detailed configuration parameters of the corresponding vehicle model are obtained from the data localized brand parts vehicle model library or the original parts vehicle model library. Based on the target vehicle model, each maintenance item and the corresponding accessory brand, the brand accessory model is obtained from the brand parts vehicle model accessories relationship library, and the detailed information of the brand parts is obtained from the accessories brand parts library, including: accessory brand, accessory model, accessory specification, brand part code, maintenance usage, etc. Based on the target vehicle model and each maintenance item, the detailed information of the original accessories is obtained from the original parts vehicle model accessories relationship library, including: standard price, labor cost, OE number, etc. The branded parts maintenance items and / or original parts maintenance items are matched through the maintenance item library to determine the accessories products that need to be purchased. Based on the accessories products that need to be purchased and their detailed information, a supplier accessories library is formed to obtain the final cost price of each accessory.

[0072] In some embodiments, querying a vehicle model database based on the vehicle brand and model to obtain a brand load characteristic matrix includes:

[0073] Query the vehicle model database according to the vehicle brand and model to obtain the speed ratio coefficient and load factor of the target vehicle model;

[0074] Construct the brand load characteristic matrix based on the speed ratio coefficient and load coefficient.

[0075] The calculation method of the speed ratio coefficient and the load coefficient is as follows:

[0076]

[0077] Among them, α represents the speed ratio coefficient, R avg It represents the historical average speed of the target vehicle model, which can be determined by obtaining the historical speed data of the same model of vehicles through the Internet of Vehicles platform. econ The middle value of the economic speed range of the target vehicle model can be expressed by extracting the economic speed range from the engine performance curve of the target vehicle brand model to determine the middle value of the economic speed range of the target vehicle model.

[0078]

[0079] Where β represents the load factor, Wmedian The median load distribution of the target vehicle model can be determined by counting the typical load distribution of users through the vehicle mass sensor. max Indicates the maximum design load of the target vehicle model, which can be obtained from the vehicle technical specifications.

[0080] The speed ratio coefficient is used to reflect the degree to which the speed deviates from the economic range during driving, and the load factor is used to quantify the engine load intensity.

[0081] S3. Calculate the driving wear index based on the brand load characteristic matrix.

[0082] The driving wear index calculation method integrates the principles of mechanical dynamics and data-driven methods. It evaluates the risk of mechanical wear by comprehensively considering the synergistic effect of speed and load, and achieves an upgrade from a single mileage dimension to a wear assessment that couples multiple physical fields. For example, when the speed ratio coefficient is high, the friction between the piston ring and the cylinder wall intensifies, the deterioration of the engine oil accelerates, and the impact load of the valve mechanism (such as the camshaft and rocker arm) increases; when the load coefficient is high, the temperature of the combustion chamber rises, resulting in carbon deposits and wear of the cylinder coating, and the crankshaft bearings and connecting rods are subjected to greater shear stress. The driving wear index is used to reflect maintenance strategies under different driving behaviors. For example, under driving behaviors with a high driving wear index, priority items may include replacing high-performance fully synthetic engine oil, checking the sealing of the turbocharger, and cleaning carbon deposits on the intake valve; under driving behaviors with a low driving wear index, it may be allowed to extend the oil life and air filter replacement cycle.

[0083] In some embodiments, the calculation formula for calculating the driving wear index based on the brand load characteristic matrix is ​​as follows:

[0084] Δm=m p -m0;

[0085]

[0086] Where W represents the driving wear index, Δm represents the difference between the preset maintenance mileage and the initial mileage, and m p represents the preset maintenance mileage, m0 represents the initial mileage, α represents the speed ratio coefficient, β represents the load coefficient, D1 represents the speed item wear increment coefficient, and D2 represents the load item wear increment coefficient.

[0087] Among them, the speed item wear increment coefficient is used to standardize the effect of engine speed on component life into the mileage dimension. The longer the high-speed operation time, the more serious the friction and wear. The cumulative effect is quantified by mileage equivalent. It is set according to the actual situation. For example, D1 can be set to 1000, which represents the cumulative amount of speed-related wear per 1000 kilometers. The load item wear increment coefficient is used to reflect the accelerated loss of transmission gears, suspension systems, etc. under heavy load conditions. The greater the load, the higher the gear contact stress, and the fatigue life is nonlinearly shortened. It is set according to the actual situation. For example, D2 can be set to 500, which represents the load-related wear increment every 500 kilometers.

[0088] S4. Calculate the dynamic compensation mileage threshold of each maintenance item based on the driving wear index.

[0089] In some embodiments, the calculation formula for calculating the dynamic compensation mileage threshold of each maintenance item based on the driving wear index is as follows:

[0090]

[0091] in, represents the mileage threshold after dynamic compensation of the kth maintenance item, Indicates the baseline mileage of the kth maintenance item.

[0092] The dynamic compensation mileage threshold is calculated using a semi-logarithmic function model, ensuring a nonlinear relationship between the wear index and the mileage adjustment. For example, when the wear index W is 0.5, the adjusted threshold for a project with a base mileage of 10,000 kilometers is 10,000 × (1 - 0.1 × ln1.5) ≈ 9,430 kilometers. This logarithmic function significantly impacts the threshold with increased initial wear, while the adjustment is more gradual under extreme wear conditions, thus preventing excessive maintenance frequency due to extreme driving behavior.

[0093] S5. Compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items.

[0094] In some embodiments, S5 includes the following sub-steps:

[0095] S51, calculating the maintenance coefficient of each maintenance item based on the difference between the preset maintenance mileage and the initial mileage, the dynamic compensation mileage threshold, and the life coefficient of each accessory;

[0096] The calculation formula is as follows:

[0097]

[0098] Among them, N k represents the maintenance coefficient of the kth maintenance item, q kIndicates the life coefficient of the accessory corresponding to the kth maintenance item.

[0099] The maintenance project decision algorithm introduces a double verification mechanism, with the life coefficient as the basic threshold for project necessity and the dynamic compensation threshold as the trigger condition for actual demand. When the actual mileage of the vehicle reaches a certain ratio of the compensation threshold, the system generates a maintenance recommendation at the warning level. First, compare the ratio of Δm to the dynamic compensation threshold. For example, if the adjusted threshold of a brake pad project is 8,000 kilometers and the user's planned mileage difference is 7,000 kilometers, the ratio is 7,000 / 8,000 = 0.875. If the life coefficient q of the accessory of the project k is 0.9, then 0.875<0.9, the maintenance coefficient is 0, and the system determines that no immediate maintenance is required.

[0100] S52: Export maintenance items with a maintenance coefficient of 1 and generate a recommended maintenance item list.

[0101] S6. Calculate the cost of each maintenance item and the total cost based on the recommended maintenance item list.

[0102] Specifically, the cost of each maintenance item is determined based on the recommended maintenance item list and the cost price of each accessory corresponding to each maintenance item;

[0103] The total cost is obtained by summing the costs of each maintenance item in the recommended maintenance item list.

[0104] In some embodiments, the cost calculation engine employs a multi-dimensional pricing strategy. The cost price is composed of the original manufacturer's and / or branded parts' prices and labor costs. The system can also automatically calculate and apply discount factors to generate the optimal price solution and display the gross profit margin for each product.

[0105] In some embodiments, after a quotation is generated, the system automatically compares quotations from service providers in the same region to achieve transparent service quotations.

[0106] The present invention automatically adapts to corresponding maintenance services based on the vehicle model robustness matching mechanism, saving employees' analysis time costs. Through a nonlinear mileage compensation algorithm and the calculation of the driving wear index driven by brand characteristics, and by analyzing the coupling effect of the speed ratio coefficient and the load coefficient, the recommended cycle of each maintenance item is dynamically adjusted to avoid excessive or insufficient maintenance caused by traditional fixed-cycle maintenance. The actual working conditions of the vehicle are combined with the manufacturer's recommended standards through a standardized service system, thus achieving precise and personalized vehicle maintenance. The vehicle model database integrates accessories and maintenance service quotations, visualizes the maintenance item decision-making process, reduces service costs, and improves the decision-making flexibility of car owners, ultimately forming an intelligent maintenance decision-making support capability in the dimension of the entire life cycle.

[0107] See also Figure 4-Figure 6This is the actual operation page of the "Tiantianpao" product provided by this invention. First, enter the "Tiantianpao" business interface from the Tiantianpao mini-program. After entering the initial mileage, click Get Quote to jump to the product quotation page. You can drag the cart to change the preset maintenance mileage. The system automatically calculates the maintenance items and accessories based on the algorithm. You can also manually select alternative maintenance items and accessories to automatically calculate the price of the maintenance items and display the cost price and product description of the required accessories. Check the Tiantianpao agreement, read and agree, then you can make the purchase, submit the order, and make the payment. The purchase is successful. After purchasing the product, you can view the annual maintenance card voucher information in the service package; click on any maintenance service to enter the details page to view the card voucher. Clicking the card voucher will enter the QR code page for offline verification. Present the QR code when using it in the store. The 4S store will create a work order. Scan the QR code for verification. The work order will automatically bring up the corresponding maintenance items and repair parts, and generate a verification record. By clicking the Usage Record button on the operation interface, you can view the usage status of the service (remaining times, number of times used).

[0108] The "Daily Run" product offered by this invention provides comprehensive, customized discount plans for basic maintenance services based on vehicle mileage, combined with multiple factors such as the brand manufacturer's maintenance manual, the vehicle's actual usage environment, and the owner's driving habits. This feature, compared to the one-size-fits-all maintenance services of existing technologies, better meets the personalized needs of vehicle owners and improves maintenance effectiveness.

[0109] The "Tiantianpao" product can also provide a variety of scenarios such as public service car maintenance, community car maintenance, 4S shop car maintenance, etc., and is equipped with door-to-door pick-up and delivery services, allowing car owners to choose appropriate maintenance methods according to their needs and time arrangements, greatly improving the convenience and flexibility of maintenance.

[0110] Leveraging over 20 years of industry experience and data from over one million vehicles, this product has established a standardized service system, from vehicle information collection and registration to after-sales service, ensuring the quality and efficiency of maintenance services. This transparent management approach, with traceable products, full-process visualization, and team-verifiable capabilities, allows car owners to clearly understand the entire maintenance process, enhancing service credibility and satisfaction. Covering all brands of gasoline, hybrid, and pure electric vehicles, car owners only need to perform simple operations, and the system will quickly identify vehicle information and generate customized maintenance discount plans, eliminating scams and hidden costs and ensuring a clear understanding of maintenance costs.

[0111] This product makes vehicle maintenance more accurate and effective through customized services, extending the vehicle's service life; the standardized service system and convenient quotation system shorten service time and improve service efficiency; transparent management and diversified scenario solutions enhance car owners' sense of trust and satisfaction; customized maintenance discount plans enable car owners to enjoy high-quality maintenance services at a lower cost.

[0112] The embodiment of the present invention also provides a mileage-based vehicle maintenance dynamic recommendation system based on driving behavior, which is used to execute the above-mentioned mileage-based vehicle maintenance dynamic recommendation method. Figure 7 This is a structural diagram of a dynamic vehicle maintenance recommendation system based on mileage dimension of driving behavior provided by an embodiment of the present invention. Figure 7 , the system includes the following modules:

[0113] The data acquisition module is used to obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user; the vehicle series and model are not required and can be matched at the smallest granularity;

[0114] The matching module is used to query the vehicle model database based on the vehicle brand and model to obtain the standard maintenance item table and brand load characteristic matrix;

[0115] A calculation module, configured to calculate a driving wear index based on a brand load characteristic matrix; and to calculate a dynamic compensation mileage threshold for each maintenance item based on the driving wear index;

[0116] The maintenance item recommendation module is used to compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items;

[0117] The maintenance cost calculation module is used to calculate the cost of each maintenance item and the total cost based on the recommended maintenance item list.

[0118] Furthermore, the dynamic vehicle maintenance recommendation system based on mileage and driving behavior also includes:

[0119] Worry-free project module, including basic service construction such as maintenance services, travel services, insurance services, other services, comprehensive services, project formulas, etc.

[0120] Discount coefficient module, used to maintain customized discount coefficients based on vehicle model matching results and business versions;

[0121] The product gross profit margin module is used to maintain customized gross profit margins based on vehicle model matching results and business versions.

[0122] In some embodiments, the maintenance cost calculation module calculates the cost of each maintenance item and the total cost based on the recommended maintenance item list, the discount factor, and the gross profit margin.

[0123] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A dynamic vehicle maintenance recommendation method based on mileage and driving behavior, characterized by: The method comprises the following steps: S1. Obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user; S2. Querying a vehicle model database based on the vehicle brand and model to obtain a standard maintenance item table and a brand load characteristic matrix; S3. Calculating a driving wear index according to the brand load characteristic matrix; S4. Calculating a dynamic compensation mileage threshold for each maintenance item based on the driving wear index; S5. Compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items; S6. Calculate the cost of each maintenance item and the total cost according to the recommended maintenance item list.

2. The mileage-based vehicle maintenance dynamic recommendation method based on driving behavior according to claim 1 is characterized in that: In S2, querying the vehicle model database based on the vehicle brand and model to obtain a standard maintenance item list includes: Query the vehicle model database according to the vehicle brand and model to obtain all maintenance items of the target vehicle model; The base mileage corresponding to the maintenance items, the life coefficient of each accessory, and the cost price of each accessory are obtained to construct a maintenance item table.

3. The mileage-based dynamic vehicle maintenance recommendation method based on driving behavior according to claim 2 is characterized in that: The calculation formula of the life coefficient of each accessory is as follows: Among them, q k Indicates the life coefficient of the accessory corresponding to the kth maintenance item, represents the base mileage corresponding to the kth maintenance item, It represents the average maintenance mileage of the accessories corresponding to the k-th maintenance item.

4. The mileage-based vehicle maintenance dynamic recommendation method based on driving behavior according to claim 1 is characterized in that: In S2, querying the vehicle model database based on the vehicle brand model to obtain the brand load characteristic matrix includes: Querying a vehicle model database according to the vehicle brand and model to obtain a speed ratio coefficient and a load coefficient of a target vehicle model; Construct the brand load characteristic matrix based on the speed ratio coefficient and load coefficient.

5. The mileage-based dynamic vehicle maintenance recommendation method based on driving behavior according to claim 4 is characterized in that: The calculation method of the speed ratio coefficient and the load factor is as follows: Among them, α represents the speed ratio coefficient, R avg represents the historical average speed of the target vehicle model, R econ Indicates the middle value of the economic speed range of the target vehicle model; Where β represents the load factor, W median Represents the median load distribution of the target vehicle type, W max Indicates the maximum design load of the target vehicle type.

6. The mileage-based vehicle maintenance dynamic recommendation method based on driving behavior according to claim 4 is characterized in that: In S3, the calculation formula for the driving wear index based on the brand load characteristic matrix is ​​as follows: Δm=m p -m0; Where W represents the driving wear index, Δm represents the difference between the preset maintenance mileage and the initial mileage, and m p represents the preset maintenance mileage, m0 represents the initial mileage, α represents the speed ratio coefficient, β represents the load coefficient, D1 represents the speed item wear increment coefficient, and D2 represents the load item wear increment coefficient.

7. The mileage-based dynamic vehicle maintenance recommendation method based on driving behavior according to claim 6 is characterized in that: In S4, the calculation formula for calculating the dynamic compensation mileage threshold of each maintenance item based on the driving wear index is as follows: in, represents the mileage threshold after dynamic compensation of the kth maintenance item, Indicates the baseline mileage of the kth maintenance item.

8. The mileage-based dynamic vehicle maintenance recommendation method based on driving behavior according to claim 7 is characterized in that: In S5, the difference between the preset maintenance mileage and the initial mileage is compared with the dynamic compensation mileage threshold to generate a list of recommended maintenance items, including: Among them, N k represents the maintenance coefficient of the kth maintenance item, q k Indicates the life coefficient of the accessory corresponding to the kth maintenance item; Export the maintenance items with a maintenance factor of 1 and generate a list of recommended maintenance items.

9. The mileage-based dynamic vehicle maintenance recommendation method based on driving behavior according to claim 2 is characterized in that: In S6, calculating the cost of each maintenance item and the total cost according to the recommended maintenance item list includes: Determine the cost of each maintenance item based on the recommended maintenance item list and the cost price of each accessory corresponding to each maintenance item; The total cost is obtained by summing the costs of each maintenance item in the recommended maintenance item list.

10. A mileage-based vehicle maintenance dynamic recommendation system based on driving behavior, configured to execute the mileage-based vehicle maintenance dynamic recommendation method based on driving behavior according to any one of claims 1 to 9, characterized in that: The system includes the following modules: The data acquisition module is used to obtain the vehicle brand and model, initial mileage, and preset maintenance mileage input by the user; A matching module, configured to query a vehicle model database based on the vehicle brand and model to obtain a standard maintenance item table and a brand load characteristic matrix; A calculation module, configured to calculate a driving wear index based on the brand load characteristic matrix; and to calculate a dynamic compensation mileage threshold for each maintenance item based on the driving wear index; a maintenance item recommendation module, configured to compare the difference between the preset maintenance mileage and the initial mileage with the dynamic compensation mileage threshold to generate a list of recommended maintenance items; The maintenance cost calculation module is used to calculate the cost of each maintenance item and the total cost according to the recommended maintenance item list.

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