Second-hand automobile market price evaluation method

Abstract

The invention discloses a second-hand automobile market price assessment method, and relates to the technical field of price assessment, and the method comprises the following steps: through a chassis dynamometer, an engine comprehensive detector, an oil consumption detector and a brake detection bench, detecting and obtaining the engine power, the oil consumption per hundred kilometers and the brake distance of a current to-be-assessed second-hand automobile; the method comprises the following steps: collecting reference parameter data of a current to-be-evaluated second-hand automobile, including automobile age and mileage, establishing a second-hand automobile database through MySQL, establishing a file by combining the collected data of the current to-be-evaluated second-hand automobile with engine power, fuel consumption per hundred kilometers and braking distance, and summarizing the file into the second-hand automobile database. According to the method, the evaluation value of the second-hand automobile is reasonably adjusted through basic automobile condition evaluation and regional value compensation and by comprehensively considering the market requirements of the brand and color of the current second-hand automobile and the influence of regional characteristics, so that the final second-hand automobile identification price is more accurate and fair.

Description

Technical Field

[0001] The present invention relates to the technical field of price evaluation, and in particular to a method for evaluating the market price of a used car. Background Art

[0002] Second-hand cars refer to vehicles that have been used. These cars may have been used by one or more owners for a period of time and then sold through various channels. Second-hand cars can be traded between individuals or sold through channels such as second-hand car dealers or auction houses.

[0003] In the process of selling used cars, it is often necessary to identify various parameters of used cars in order to assess the value of the relevant used cars. Existing used car evaluations are mostly based on subjective human value assessments and determinations, which have limitations and cannot be combined with specific parameters of similar used vehicles for horizontal comparison. It is also impossible to conduct a comprehensive pricing of the used car value based on relevant specific data of the used car's use area, and there are problems with low practicality and functionality.

[0004] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0005] In view of the problems in the related art, the present invention proposes a second-hand car market price evaluation method to overcome the above technical problems existing in the existing related art.

[0006] To this end, the specific technical solution adopted by the present invention is as follows:

[0007] A method for evaluating the market price of a used car comprises the following steps:

[0008] S1. Use chassis dynamometer, engine comprehensive tester, fuel consumption tester and brake test bench to test and obtain the engine power, fuel consumption per 100 kilometers and braking distance of the second-hand car to be evaluated;

[0009] S2. Collect the benchmark parameter data of the second-hand cars to be evaluated, including the age and mileage of the car, establish a second-hand car database through MySQL, combine the collected data of the second-hand cars to be evaluated with the engine power, fuel consumption per 100 kilometers, and braking distance to create a file, and summarize the file into the second-hand car database;

[0010] S3. Collect data from the second-hand car sales platform, combine the engine performance, fuel consumption performance, braking performance, vehicle age, and mileage in the second-hand car files to be evaluated, evaluate and identify the second-hand car to be evaluated, and comprehensively evaluate the mechanical performance score and basic parameter score to obtain a benchmark evaluation score;

[0011] S4. Collect the brand and color of the second-hand car to be evaluated, integrate the sales data of vehicles of the same level on the second-hand car sales platform, adjust the specific score of the current vehicle, and based on the usage area of ​​the second-hand car to be evaluated, collect the vehicle type and value range in the current area, adjust the regional score of the current vehicle, and obtain the final value estimation range of the second-hand car to be evaluated.

[0012] As a preferred embodiment, S3 comprises the following steps:

[0013] S31. Collect data from current second-hand car sales platforms, collect statistics on the engine performance, fuel consumption performance, and braking performance of vehicles on sale under the current second-hand car models to be evaluated, divide the score range based on the mean and standard deviation, and perform mechanical performance scoring on the current second-hand cars to be evaluated;

[0014] S32. Calculate the basic parameter score based on the age and mileage of the used car in the current used car file to be evaluated and the retirement and scrapping standards for private cars. Combine the mechanical performance score and the basic parameter score to generate the benchmark appraisal score for the current used car to be evaluated.

[0015] As a preferred implementation, the S31 includes the following steps:

[0016] S311. Use a crawler to crawl the engine performance, fuel consumption performance, and braking performance of the vehicles on sale under the second-hand car model to be evaluated from the second-hand car sales platform, including engine power, fuel consumption per 100 kilometers, and braking distance, and calculate the mean and standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance. The algorithm formula is:

[0017]

[0018] in, They represent the average engine power, average fuel consumption per 100 kilometers, and average braking distance of the second-hand car models currently on sale for evaluation. P 、N H 、N S is the sample size;

[0019] Represent the i-th sample of engine power, fuel consumption per 100 kilometers, and braking distance, σ P , σ H , σ S They represent the standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance of the second-hand car models to be evaluated;

[0020] S312, divide the current second-hand car model into score intervals by using the mean and standard deviation, and score the current second-hand car to be evaluated based on its engine power P, fuel consumption per 100 kilometers H, and braking distance S. The specific steps are as follows:

[0021] when When the engine power score of the second-hand car to be evaluated is recorded, P =100, fuel consumption per 100 kilometers ω H =100, braking distance score ω S =100;

[0022] when When the engine power score of the second-hand car to be evaluated is recorded, P =90, fuel consumption per 100 kilometers ω H =90, braking distance score ω S =90;

[0023] when When the engine power score of the second-hand car to be evaluated is recorded, P =80, fuel consumption per 100 kilometers ω H =80, braking distance score ω S =80;

[0024] when When the engine power score of the second-hand car to be evaluated is recorded, P =70, fuel consumption per 100 kilometers ω H =70, braking distance score ω S =70;

[0025] when When the engine power score of the second-hand car to be evaluated is recorded, P =60, fuel consumption per 100 kilometers ω H =60, braking distance score ω S =60.

[0026] As a preferred embodiment, the S32 comprises the following steps:

[0027] S321, collecting the vehicle age α and mileage β in the files of the second-hand car to be evaluated, dividing the score range based on the retirement and scrapping standards of private cars, and calculating the vehicle age score and mileage score of the second-hand car to be evaluated. The specific steps are as follows:

[0028] When α≤2, β≤10, record the age score of the second-hand car to be evaluated ω α =100, the mileage score of the second-hand car to be evaluated β =100;

[0029] When 2<α≤4, 10<β≤20, then record the age score of the current second-hand car to be evaluated ω α =85, Mileage of the current used car to be evaluatedω β =85;

[0030] When 4<α≤6, 20<β≤30, then record the age score of the current second-hand car to be evaluated ω α =70, the current mileage score of the second-hand car to be evaluatedω β =70;

[0031] When 6<α≤8, 30<β≤40, then record the age score of the second-hand car to be evaluated ω α =55, Mileage of the current used car to be evaluatedω β =55;

[0032] When α>8、β>40, record the age score of the second-hand car to be evaluated ω α =40, the current mileage score of the second-hand car to be evaluatedω β =40;

[0033] S322. Based on the vehicle age α and mileage β coefficient ratio in the used vehicle file, calculate the basic parameter score λ of the current used vehicle to be evaluated. The algorithm formula is:

[0034] λ=δ1·ω α +δ2·ω β ;

[0035] Among them, δ1 and δ2 are the vehicle age and mileage coefficient ratios, with values ​​of 0.3 and 0.7 respectively;

[0036] The mechanical performance score is calculated based on the engine power score ratio, the fuel consumption per 100 kilometers score ratio, and the braking distance score ratio. The basic parameter score is combined to obtain the benchmark appraisal score of the second-hand car to be evaluated. The algorithm formula is:

[0037] η=(γ1·ω P +γ2·ω H +γ3·ω S )·0.5+λ·0.5;

[0038] Among them, η is the benchmark appraisal score of the current used car to be evaluated, γ1, γ2, and γ3 represent the proportion of engine power score, the proportion of fuel consumption per 100 kilometers, and the proportion of braking distance score, with values ​​of 0.3, 0.4, and 0.4 respectively.

[0039] As a preferred embodiment, the S4 includes the following sub-steps:

[0040] S41. Collect brand and color data of the second-hand cars to be evaluated, including brands of German, American, Japanese, French, Korean and domestic brands. Summarize the sales data of different categories of vehicles of the same level on the second-hand car sales platform, calculate the proportion of vehicles of different categories, and count the proportion of vehicle colors in the current vehicle category proportion to calculate the additional score of the second-hand car category to be evaluated;

[0041] S42. Based on the current usage region of the used car to be evaluated, the vehicle type ratio and value range ratio in the current region are collected to calculate the regional additional points of the current used car.

[0042] As a preferred implementation, the S41 includes the following steps:

[0043] S411. Collect the brands and colors of the second-hand cars to be evaluated, and obtain the sales data of vehicles of the same price from the second-hand car sales platform, including the total sales of vehicles of the same price and the individual sales of different brands at the current price. Calculate the sales proportion of German, American, Japanese, French, Korean and domestic second-hand cars at the current price of the second-hand cars to be evaluated. The algorithm formula is:

[0044]

[0045] Based on the proportion of German, American, Japanese, French, Korean and domestic cars in the current price range, German, American, Japanese, French, Korean and domestic cars are arranged in descending order, and the brand score of the first brand is recorded as 10 points, the brand score of the second brand is 8 points, the brand score of the third brand is 6 points, and the brand score of the fourth brand is 4 points. The scores of the others are not recorded. The brand of the second-hand car to be evaluated is matched and the brand score is recorded;

[0046] S412. Collect vehicle color data within the current brand share, and calculate the sales share of different colors within the same brand. The algorithm formula is:

[0047]

[0048] Arrange in descending order based on the color proportion, record the first color as 10 points, the second color as 8 points, the third color as 6 points, the fourth color as 4 points, the fifth color as 2 points, and do not record the rest. Match the color of the current used car to be evaluated and record the color score;

[0049] The brand score and color score of the second-hand car to be evaluated are combined to obtain the additional score A of the second-hand car category to be evaluated. The algorithm formula is:

[0050] A = current second-hand car color score + current second-hand car brand score.

[0051] As a preferred implementation, the S42 comprises the following steps:

[0052] S421. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicle types on the used car sales platform in the current region is counted. Vehicle types include SUV, sedan, hunting suit, sports car, MPV, and van. The sales percentage of different types of vehicles in the current region is calculated respectively. The type score of the current used cars is calculated. The specific steps are as follows:

[0053]

[0054] Based on the proportion of second-hand sales of SUVs, sedans, shooting brakes, sports cars, MPVs, and vans in the current region, SUVs, sedans, shooting brakes, sports cars, MPVs, and vans are sorted in descending order, and the first type is scored 10 points, the second type is scored 8 points, the third type is scored 6 points, the fourth type is scored 4 points, and the rest are not recorded. Match the type of the current second-hand car to be evaluated and record the type score;

[0055] S422. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicles in the current region in the used car sales platform in the price range is counted, where the price range is divided into a range of 25,000 yuan each, and the sales percentage of used cars in different price ranges in the current region is calculated respectively, and the price score of the current used cars is calculated. The specific steps are as follows:

[0056]

[0057] Based on the sales volume of used vehicles in different price ranges in the current region, the price ranges are sorted in descending order, and the price of the first range is recorded as 10 points, the price of the second range is 8 points, the price of the third range is 6 points, the price of the fourth range is 4 points, and the price of the fifth range is 2 points. The rest are not recorded. The price range of the current used car to be evaluated is matched and the price score is recorded;

[0058] The type score and price score of the second-hand car to be evaluated are combined to obtain the regional additional score B of the second-hand car to be evaluated. The algorithm formula is:

[0059] B = current second-hand car type score × 0.7 + current second-hand car price score × 0.3;

[0060] The regional compensation score C of the second-hand car to be evaluated is obtained by combining the category additional score A and the regional additional score B of the second-hand car to be evaluated. The algorithm formula is:

[0061] C = (A + B) × 0.75;

[0062] Based on the regional compensation score C of the current used car to be evaluated, the benchmark appraisal score of the current used car to be evaluated is compensated.

[0063] As a preferred implementation, the S422 includes the following steps:

[0064] S4221, the comprehensive benchmark appraisal score and the regional compensation score are used to generate the comprehensive appraisal score θ of the second-hand car to be evaluated. The algorithm formula is:

[0065] θ = η + C;

[0066] Record the comprehensive appraisal score θ and enter it into the file of the second-hand car to be evaluated. Based on the lowest and highest prices of the second-hand car models to be evaluated on the market, calculate the total span of the price range. Divide the total span into 100 equal parts to obtain the price span h. Calculate the final value of the second-hand car to be evaluated based on the comprehensive appraisal score θ:

[0067] V = lowest price + (θ-0.5) × h;

[0068] Here V represents the final value of the used car currently to be evaluated.

[0069] The beneficial effects of the present invention are:

[0070] 1. The present invention combines the relevant data of the current second-hand car sales platform to comprehensively evaluate the engine performance, fuel consumption performance, braking performance, vehicle age, and mileage of the current second-hand car, and comprehensively evaluates the mechanical performance score and the basic parameter score to obtain the benchmark appraisal score, objectively evaluate the actual vehicle condition of the current second-hand car, and use the actual data of the current second-hand car sales platform for evaluation, so that the appraisal result is more convincing;

[0071] 2. The present invention calculates the category extra points of current used cars based on the category and color of the current used cars and the actual sales situation in the current used car sales area, which can more accurately reflect the preferences of consumers in the region for vehicles of different categories and colors, help used cars obtain evaluation pricing that better meets market demand, and enhance functionality;

[0072] 3. The present invention calculates the regional extra points for the current second-hand car by combining the actual vehicle type sales ratio and price range sales ratio in the current region, and generates regional compensation points by integrating the category extra points and the regional extra points, and performs regional compensation on the current second-hand car benchmark appraisal points. According to the vehicle type sales ratio and price range sales ratio in different regions, the final value of the vehicle is dynamically adjusted, so that the price of the vehicle is more in line with the local market conditions, and the accuracy of the appraisal value is enhanced;

[0073] 4. The present invention improves the transparency of second-hand car transactions and reduces information asymmetry by calculating the benchmark appraisal score of the current second-hand vehicle, and can quickly understand the real condition of the vehicle based on the benchmark appraisal score, thereby enhancing practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0075] Figure 1 The present invention is a flowchart of a method for evaluating the market price of a used car according to an embodiment of the present invention. DETAILED DESCRIPTION

[0076] To further illustrate each embodiment, the present invention provides drawings, which are part of the disclosure of the present invention and are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in the field should be able to understand other possible implementations and advantages of the present invention. The components in the figures are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0077] According to an embodiment of the present invention, a method for evaluating market price of a used car is provided.

[0078] The present invention is further described with reference to the accompanying drawings and specific embodiments:

[0079] Embodiment 1:

[0080] like Figure 1 As shown, a second-hand car market price evaluation method according to an embodiment of the present invention comprises the following steps:

[0081] S1. Use chassis dynamometer, engine comprehensive tester, fuel consumption tester and brake test bench to test and obtain the engine power, fuel consumption per 100 kilometers and braking distance of the second-hand car to be evaluated;

[0082] S2. Collect the benchmark parameter data of the second-hand cars to be evaluated, including the age and mileage of the car, establish a second-hand car database through MySQL, combine the collected data of the second-hand cars to be evaluated with the engine power, fuel consumption per 100 kilometers, and braking distance to create a file, and summarize the file into the second-hand car database;

[0083] S3. Collect data from the second-hand car sales platform, combine the engine performance, fuel consumption performance, braking performance, vehicle age, and mileage in the second-hand car files to be evaluated, evaluate and identify the second-hand car to be evaluated, and comprehensively evaluate the mechanical performance score and basic parameter score to obtain a benchmark evaluation score;

[0084] S31. Collect data from current second-hand car sales platforms, collect statistics on the engine performance, fuel consumption performance, and braking performance of vehicles on sale under the current second-hand car models to be evaluated, divide the score range based on the mean and standard deviation, and perform mechanical performance scoring on the current second-hand cars to be evaluated;

[0085] S311. Use a crawler to crawl the engine performance, fuel consumption performance, and braking performance of the vehicles on sale under the second-hand car model to be evaluated from the second-hand car sales platform, including engine power, fuel consumption per 100 kilometers, and braking distance, and calculate the mean and standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance. The algorithm formula is:

[0086]

[0087] in, They represent the average engine power, average fuel consumption per 100 kilometers, and average braking distance of the second-hand car models currently on sale for evaluation. P 、N H 、N S is the sample size;

[0088] Represent the i-th sample of engine power, fuel consumption per 100 kilometers, and braking distance, σ P , σ H , σ S They represent the standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance of the second-hand car models to be evaluated;

[0089] S312, divide the current second-hand car model into score intervals by using the mean and standard deviation, and score the current second-hand car to be evaluated based on its engine power P, fuel consumption per 100 kilometers H, and braking distance S. The specific steps are as follows:

[0090] when When the engine power score of the second-hand car to be evaluated is recorded, P =100, fuel consumption per 100 kilometers ω H =100, braking distance score ω S =100;

[0091] when When the engine power score of the second-hand car to be evaluated is recorded, P =90, fuel consumption per 100 kilometers ωH =90, braking distance score ω S =90;

[0092] when When the engine power score of the second-hand car to be evaluated is recorded, P =80, fuel consumption per 100 kilometers ω H =80, braking distance score ω S =80;

[0093] when When the engine power score of the second-hand car to be evaluated is recorded, P =70, fuel consumption per 100 kilometers ω H =70, braking distance score ω S =70;

[0094] when When the engine power score of the second-hand car to be evaluated is recorded, P =60, fuel consumption per 100 kilometers ω H =60, braking distance score ω S =60;

[0095] It should be noted that by integrating the current vehicle model sales data on the used car platform, the current vehicle's engine power, fuel consumption per 100 kilometers and braking distance can be divided into different states. By calculating the mean and standard deviation of the engine power, fuel consumption per 100 kilometers and braking distance in the used car platform sales data, the scoring range is divided. The higher the engine power, the stronger the vehicle's dynamic performance, while the lower the braking distance and fuel consumption per 100 kilometers, the more effective the braking performance and the higher the fuel economy, so as to evaluate the current market mechanical performance value of used cars.

[0096] S32. Calculate the basic parameter score based on the age and mileage of the current second-hand car to be evaluated in the file and the retirement and scrapping standards of private cars, and generate the benchmark appraisal score of the current second-hand car to be evaluated by combining the mechanical performance score and the basic parameter score;

[0097] S321, collecting the vehicle age α and mileage β in the files of the second-hand car to be evaluated, dividing the score range based on the retirement and scrapping standards of private cars, and calculating the vehicle age score and mileage score of the second-hand car to be evaluated. The specific steps are as follows:

[0098] When α≤2, β≤10, record the age score of the second-hand car to be evaluated ω α =100, the mileage score of the second-hand car to be evaluated β =100;

[0099] When 2<α≤4, 10<β≤20, then record the age score of the current second-hand car to be evaluated ωα =85, Mileage of the current used car to be evaluatedω β =85;

[0100] When 4<α≤6, 20<β≤30, then record the age score of the current second-hand car to be evaluated ω α =70, the current mileage score of the second-hand car to be evaluatedω β =70;

[0101] When 6<α≤8, 30<β≤40, then record the age score of the second-hand car to be evaluated ω α =55, Mileage of the current used car to be evaluatedω β =55;

[0102] When α>8、β>40, record the age score of the second-hand car to be evaluated ω α =40, the current mileage score of the second-hand car to be evaluatedω β =40;

[0103] S322. Based on the vehicle age α and mileage β coefficient ratio in the used vehicle file, calculate the basic parameter score λ of the current used vehicle to be evaluated. The algorithm formula is:

[0104] λ=δ1·ω α +δ2·ω β ;

[0105] Among them, δ1 and δ2 are the vehicle age and mileage coefficient ratios, with values ​​of 0.3 and 0.7 respectively;

[0106] The mechanical performance score is calculated based on the engine power score ratio, the fuel consumption per 100 kilometers score ratio, and the braking distance score ratio. The basic parameter score is combined to obtain the benchmark appraisal score of the second-hand car to be evaluated. The algorithm formula is:

[0107] η=(γ1·ω P +γ2·ω H +γ3·ω S )·0.5+λ·0.5;

[0108] Among them, η is the benchmark appraisal score of the current used car to be evaluated, γ1, γ2, and γ3 represent the proportion of engine power score, the proportion of fuel consumption per 100 kilometers, and the proportion of braking distance score, with values ​​of 0.3, 0.4, and 0.4 respectively.

[0109] It should be noted that the unit of vehicle age is year, the unit of mileage is ten thousand kilometers, δ1, δ2 as well as γ1, γ2, and γ3 can be flexibly adjusted according to the actual conditions of different regions. By adjusting different coefficient ratios or proportions, the evaluation can be more focused on a certain aspect. The benchmark identification score is obtained by comprehensively considering the mechanical properties and basic parameters of the current second-hand car, which is convenient for intuitively feeling the comprehensive objective vehicle condition of the current second-hand car, that is, when η>85 points, it means that the current second-hand car is in excellent objective condition; when 70<η≤85, it means that the current second-hand car is in good objective condition; when 55<η≤70, it means that the current second-hand car is in general objective condition; when 40<η≤55, it means that the current second-hand car is in poor objective condition; when η≤40, it means that the current second-hand car is in very poor objective condition.

[0110] Embodiment 2:

[0111] S4. Collect the brand and color of the second-hand car to be evaluated, integrate the sales data of vehicles of the same level on the second-hand car sales platform, adjust the specific score of the current vehicle, and based on the use area of ​​the second-hand car to be evaluated, collect the vehicle type and value range of the current region, adjust the regional score of the current vehicle, and obtain the final value estimation range of the second-hand car to be evaluated;

[0112] S41. Collect brand and color data of the second-hand cars to be evaluated, including brands of German, American, Japanese, French, Korean and domestic brands. Summarize the sales data of different categories of vehicles of the same level on the second-hand car sales platform, calculate the proportion of vehicles of different categories, and count the proportion of vehicle colors in the current vehicle category proportion to calculate the additional score of the second-hand car category to be evaluated;

[0113] S411. Collect the brands and colors of the second-hand cars to be evaluated, and obtain the sales data of vehicles of the same price from the second-hand car sales platform, including the total sales of vehicles of the same price and the individual sales of different brands at the current price. Calculate the sales proportion of German, American, Japanese, French, Korean and domestic second-hand cars at the current price of the second-hand cars to be evaluated. The algorithm formula is:

[0114]

[0115] Based on the proportion of German, American, Japanese, French, Korean and domestic cars in the current price range, German, American, Japanese, French, Korean and domestic cars are arranged in descending order, and the brand score of the first brand is recorded as 10 points, the brand score of the second brand is 8 points, the brand score of the third brand is 6 points, and the brand score of the fourth brand is 4 points. The scores of the others are not recorded. The brand of the second-hand car to be evaluated is matched and the brand score is recorded;

[0116] S412. Collect vehicle color data within the current brand share, and calculate the sales share of different colors within the same brand. The algorithm formula is:

[0117]

[0118] Arrange in descending order based on the color proportion, record the first color as 10 points, the second color as 8 points, the third color as 6 points, the fourth color as 4 points, the fifth color as 2 points, and do not record the rest. Match the color of the current used car to be evaluated and record the color score;

[0119] The brand score and color score of the second-hand car to be evaluated are combined to obtain the additional score A of the second-hand car category to be evaluated. The algorithm formula is:

[0120] A = current second-hand car color score + current second-hand car brand score;

[0121] It should be noted that the classification of vehicle grades is based on the current average price range of used cars on the used car sales platform. By screening different vehicles within the same price range and based on the brand types of these sales vehicles, the sales proportion of different brands within the same price range is determined. By comprehensively considering the current market demand for used car brands and colors, the accuracy of current used car evaluation and identification can be improved.

[0122] S42. Based on the current usage region of the used car to be evaluated, the vehicle type ratio and value range ratio in the current region are collected to calculate the regional additional score of the current used car;

[0123] S421. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicle types on the used car sales platform in the current region is counted. Vehicle types include SUV, sedan, hunting suit, sports car, MPV, and van. The sales percentage of different types of vehicles in the current region is calculated respectively. The type score of the current used cars is calculated. The specific steps are as follows:

[0124]

[0125] Based on the proportion of second-hand sales of SUVs, sedans, shooting brakes, sports cars, MPVs, and vans in the current region, SUVs, sedans, shooting brakes, sports cars, MPVs, and vans are sorted in descending order, and the first type is scored 10 points, the second type is scored 8 points, the third type is scored 6 points, the fourth type is scored 4 points, and the rest are not recorded. Match the type of the current second-hand car to be evaluated and record the type score;

[0126] S422. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicles in the current region in the used car sales platform in the price range is counted, where the price range is divided into a range of 25,000 yuan each, and the sales percentage of used cars in different price ranges in the current region is calculated respectively, and the price score of the current used cars is calculated. The specific steps are as follows:

[0127]

[0128] Based on the sales volume of used vehicles in different price ranges in the current region, the price ranges are sorted in descending order, and the price of the first range is recorded as 10 points, the price of the second range is 8 points, the price of the third range is 6 points, the price of the fourth range is 4 points, and the price of the fifth range is 2 points. The rest are not recorded. The price range of the current used car to be evaluated is matched and the price score is recorded;

[0129] The type score and price score of the second-hand car to be evaluated are combined to obtain the regional additional score B of the second-hand car to be evaluated. The algorithm formula is:

[0130] B = current second-hand car type score × 0.7 + current second-hand car price score × 0.3;

[0131] The regional compensation score C of the second-hand car to be evaluated is obtained by combining the category additional score A and the regional additional score B of the second-hand car to be evaluated. The algorithm formula is:

[0132] C = (A + B) × 0.75;

[0133] Based on the regional compensation score C of the second-hand car to be evaluated, the benchmark appraisal score of the second-hand car to be evaluated is compensated;

[0134] S4221, the comprehensive benchmark appraisal score and the regional compensation score are used to generate the comprehensive appraisal score θ of the second-hand car to be evaluated. The algorithm formula is:

[0135] θ = η + C;

[0136] Record the comprehensive appraisal score θ and enter it into the file of the second-hand car to be evaluated. Based on the lowest and highest prices of the second-hand car models to be evaluated on the market, calculate the total span of the price range. Divide the total span into 100 equal parts to obtain the price span h. Calculate the final value of the second-hand car to be evaluated based on the comprehensive appraisal score θ:

[0137] V = lowest price + (θ-0.5) × h;

[0138] Where V represents the final value of the used car currently to be evaluated.

[0139] It should be noted that by combining the benchmark appraisal score and the regional compensation score to generate the comprehensive appraisal score of the current used car, the objective value of the current used car and the actual sales value in the current region can be comprehensively considered, so as to generate the value of the current used car through comprehensive appraisal and evaluation, where the total span is the highest price minus the lowest price, and the total span is equally divided into shares to obtain the price span of each share.

[0140] In summary, the present invention comprehensively evaluates the engine performance, fuel consumption performance, braking performance, vehicle age, and mileage of current second-hand cars by combining relevant data from the current second-hand car sales platform, and comprehensively evaluates the mechanical performance score and the basic parameter score to obtain a benchmark appraisal score, objectively evaluate the actual vehicle condition of the current second-hand car, and uses the actual data of the current second-hand car sales platform for evaluation, so that the appraisal result is more convincing;

[0141] By calculating the category extra points of current used cars based on the categories and colors of current used cars and the actual sales situation in the current used car sales area, it can more accurately reflect the preferences of consumers in the region for vehicles of different categories and colors, help used vehicles obtain evaluation and pricing that is more in line with market demand, and enhance functionality. By combining the actual vehicle type sales share and price range sales share in the current region, regional extra points are calculated for current used cars. At the same time, regional compensation points are generated by combining the category extra points and regional extra points, and regional compensation is performed on the benchmark appraisal points of current used cars. The final value of the vehicle is dynamically adjusted according to the vehicle type sales share and price range sales share in different regions, so that the price of the vehicle is more in line with local market conditions, thereby enhancing the accuracy of the evaluation value.

[0142] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for evaluating the market price of a used car, characterized in that: The method comprises the following steps: S1. Use chassis dynamometer, engine comprehensive tester, fuel consumption tester and brake test bench to test and obtain the engine power, fuel consumption per 100 kilometers and braking distance of the second-hand car to be evaluated; S2. Collect the benchmark parameter data of the second-hand cars to be evaluated, including the age and mileage of the car, establish a second-hand car database through MySQL, combine the collected data of the second-hand cars to be evaluated with the engine power, fuel consumption per 100 kilometers, and braking distance to create a file, and summarize the file into the second-hand car database; S3. Collect data from the second-hand car sales platform, combine the engine performance, fuel consumption performance, braking performance, vehicle age, and mileage in the second-hand car files to be evaluated, evaluate and identify the second-hand car to be evaluated, and comprehensively evaluate the mechanical performance score and basic parameter score to obtain a benchmark evaluation score; S31. Collect data from current second-hand car sales platforms, collect statistics on the engine performance, fuel consumption performance, and braking performance of vehicles on sale under the current second-hand car models to be evaluated, divide the score range based on the mean and standard deviation, and perform mechanical performance scoring on the current second-hand cars to be evaluated; S311. Use a crawler to crawl the engine performance, fuel consumption performance, and braking performance of the vehicles on sale under the second-hand car model to be evaluated from the second-hand car sales platform, including engine power, fuel consumption per 100 kilometers, and braking distance, and calculate the mean and standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance. The algorithm formula is: in, They represent the average engine power, average fuel consumption per 100 kilometers, and average braking distance of the second-hand car models currently on sale for evaluation. P 、N H 、N S is the sample size; Represent the i-th sample of engine power, fuel consumption per 100 kilometers, and braking distance, σ P , σ H , σ S They represent the standard deviation of engine power, fuel consumption per 100 kilometers, and braking distance of the second-hand car models to be evaluated; S4. Collect the brand and color of the second-hand car to be evaluated, integrate the sales data of vehicles of the same level on the second-hand car sales platform, adjust the specific score of the current vehicle, and based on the usage area of ​​the second-hand car to be evaluated, collect the vehicle type and value range in the current area, adjust the regional score of the current vehicle, and obtain the final value estimation range of the second-hand car to be evaluated.

2. A second-hand car market price evaluation method according to claim 1, characterized in that: The S3 further comprises the following steps: S32. Calculate the basic parameter score based on the age and mileage of the used car in the current used car file to be evaluated and the retirement and scrapping standards for private cars. Combine the mechanical performance score and the basic parameter score to generate the benchmark appraisal score for the current used car to be evaluated.

3. A second-hand car market price evaluation method according to claim 1, characterized in that: The S31 comprises the following steps: S312, divide the current second-hand car model into score intervals by using the mean and standard deviation, and score the current second-hand car to be evaluated based on its engine power P, fuel consumption per 100 kilometers H, and braking distance S. The specific steps are as follows: when When the engine power score of the second-hand car to be evaluated is recorded, P =100, fuel consumption per 100 kilometers ω H =100, braking distance score ω S =100; when When the engine power score of the second-hand car to be evaluated is recorded, P =90, fuel consumption per 100 kilometers ω H =90, braking distance score ω S =90; when When the engine power score of the second-hand car to be evaluated is recorded, P =80, fuel consumption per 100 kilometers ω H =80, braking distance score ω S =80; when When the engine power score of the second-hand car to be evaluated is recorded, P =70, fuel consumption per 100 kilometers ω H =70, braking distance score ω S =70; when When the engine power score of the second-hand car to be evaluated is recorded, P =60, fuel consumption per 100 kilometers ω H =60, braking distance score ω S =60.

4. A second-hand car market price evaluation method according to claim 2, characterized in that: The S32 comprises the following steps: S321, collecting the vehicle age α and mileage β in the files of the second-hand car to be evaluated, dividing the score range based on the retirement and scrapping standards of private cars, and calculating the vehicle age score and mileage score of the second-hand car to be evaluated. The specific steps are as follows: When α≤2, β≤10, record the age score of the second-hand car to be evaluated ω α =100, the mileage score of the second-hand car to be evaluated β =100; When 2<α≤4, 10<β≤20, then record the age score of the current second-hand car to be evaluated ω α =85, Mileage of the current used car to be evaluatedω β =85; When 4<α≤6, 20<β≤30, then record the age score of the current second-hand car to be evaluated ω α =70, the current mileage score of the second-hand car to be evaluatedω β =70; When 6<α≤8, 30<β≤40, then record the age score of the second-hand car to be evaluated ω α =55, Mileage of the current used car to be evaluatedω β =55; When α>8、β>40, record the age score of the second-hand car to be evaluated ω α =40, the current mileage score of the second-hand car to be evaluatedω β =40; S322. Based on the vehicle age α and mileage β coefficient ratio in the used vehicle file, calculate the basic parameter score λ of the current used vehicle to be evaluated. The algorithm formula is: λ=δ1·ω α +δ2·ω β ; Among them, δ1 and δ2 are the vehicle age and mileage coefficient ratios, with values ​​of 0.3 and 0.7 respectively; The mechanical performance score is calculated based on the engine power score ratio, the fuel consumption per 100 kilometers score ratio, and the braking distance score ratio. The basic parameter score is combined to obtain the benchmark appraisal score of the second-hand car to be evaluated. The algorithm formula is: η=(γ1·ω P +γ2·ω H +γ3·ω S )·0.5+λ·0.5; Among them, η is the benchmark appraisal score of the current used car to be evaluated, γ1, γ2, and γ3 represent the proportion of engine power score, the proportion of fuel consumption per 100 kilometers, and the proportion of braking distance score, with values ​​of 0.3, 0.4, and 0.4 respectively.

5. A second-hand car market price evaluation method according to claim 1, characterized in that: The S4 comprises the following sub-steps: S41. Collect brand and color data of the second-hand cars to be evaluated, including brands of German, American, Japanese, French, Korean and domestic brands. Summarize the sales data of different categories of vehicles of the same level on the second-hand car sales platform, calculate the proportion of vehicles of different categories, and count the proportion of vehicle colors in the current vehicle category proportion to calculate the additional score of the second-hand car category to be evaluated; S42. Based on the current usage region of the used car to be evaluated, the vehicle type ratio and value range ratio in the current region are collected to calculate the regional additional points of the current used car.

6. A second-hand car market price evaluation method according to claim 5, characterized in that: The S41 comprises the following steps: S411. Collect the brands and colors of the second-hand cars to be evaluated, and obtain the sales data of vehicles of the same price from the second-hand car sales platform, including the total sales of vehicles of the same price and the individual sales of different brands at the current price. Calculate the sales proportion of German, American, Japanese, French, Korean and domestic second-hand cars at the current price of the second-hand cars to be evaluated. The algorithm formula is: Based on the proportion of German, American, Japanese, French, Korean and domestic cars in the current price range, German, American, Japanese, French, Korean and domestic cars are arranged in descending order, and the brand score of the first brand is recorded as 10 points, the brand score of the second brand is 8 points, the brand score of the third brand is 6 points, and the brand score of the fourth brand is 4 points. The scores of the others are not recorded. The brand of the second-hand car to be evaluated is matched and the brand score is recorded; S412. Collect vehicle color data within the current brand share, and calculate the sales share of different colors within the same brand. The algorithm formula is: Arrange in descending order based on the color proportion, record the first color as 10 points, the second color as 8 points, the third color as 6 points, the fourth color as 4 points, the fifth color as 2 points, and do not record the rest. Match the color of the current used car to be evaluated and record the color score; The brand score and color score of the second-hand car to be evaluated are combined to obtain the additional score A of the second-hand car category to be evaluated. The algorithm formula is: A = current second-hand car color score + current second-hand car brand score.

7. A second-hand car market price evaluation method according to claim 5, characterized in that: The S42 comprises the following steps: S421. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicle types on the used car sales platform in the current region is counted. Vehicle types include SUV, sedan, hunting suit, sports car, MPV, and van. The sales percentage of different types of vehicles in the current region is calculated respectively. The type score of the current used cars is calculated. The specific steps are as follows: Based on the proportion of second-hand sales of SUVs, sedans, shooting brakes, sports cars, MPVs, and vans in the current region, SUVs, sedans, shooting brakes, sports cars, MPVs, and vans are sorted in descending order, and the first type is scored 10 points, the second type is scored 8 points, the third type is scored 6 points, the fourth type is scored 4 points, and the rest are not recorded. Match the type of the current second-hand car to be evaluated and record the type score; S422. Based on the current region where the used cars to be evaluated are used, the sales data percentage of vehicles in the current region in the used car sales platform in the price range is counted, where the price range is divided into a range of 25,000 yuan each, and the sales percentage of used cars in different price ranges in the current region is calculated respectively, and the price score of the current used cars is calculated. The specific steps are as follows: Based on the sales volume of used vehicles in different price ranges in the current region, the price ranges are sorted in descending order, and the price of the first range is recorded as 10 points, the price of the second range is 8 points, the price of the third range is 6 points, the price of the fourth range is 4 points, and the price of the fifth range is 2 points. The rest are not recorded. The price range of the current used car to be evaluated is matched and the price score is recorded; The type score and price score of the second-hand car to be evaluated are combined to obtain the regional additional score B of the second-hand car to be evaluated. The algorithm formula is: B = current second-hand car type score × 0.7 + current second-hand car price score × 0.3; The regional compensation score C of the second-hand car to be evaluated is obtained by combining the category additional score A and the regional additional score B of the second-hand car to be evaluated. The algorithm formula is: C = (A + B) × 0.75; Based on the regional compensation score C of the current used car to be evaluated, the benchmark appraisal score of the current used car to be evaluated is compensated.

8. A second-hand car market price evaluation method according to claim 7, characterized in that: The S422 comprises the following steps: S4221, the comprehensive benchmark appraisal score and the regional compensation score are used to generate the comprehensive appraisal score θ of the second-hand car to be evaluated. The algorithm formula is: θ = η + C; Record the comprehensive appraisal score θ and enter it into the file of the second-hand car to be evaluated. Based on the lowest and highest prices of the second-hand car models to be evaluated on the market, calculate the total span of the price range. Divide the total span into 100 equal parts to obtain the price span h. Calculate the final value of the second-hand car to be evaluated based on the comprehensive appraisal score θ: V = lowest price + (θ-0.5) × h; Where V represents the final value of the used car currently to be evaluated.

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