New energy vehicle energy recovery method, system, computer and readable storage medium

Abstract

The application provides a new energy vehicle energy recovery method, system, computer and readable storage medium, the method comprises the following steps: calculating a non-ramp target coasting deceleration and a ramp target coasting deceleration; calculating the road slope of the current driving road of the vehicle, and judging whether the current driving road belongs to the ramp working condition according to the road slope; calculating the vehicle weight of the vehicle; calculating the coasting recovery request torque of the vehicle according to the current coasting deceleration of the vehicle, the road slope and the vehicle weight of the vehicle, and recovering energy and generating energy recovery strength according to the coasting recovery request torque of the vehicle, the application is suitable for different driving habits of drivers and is suitable for different road congestion and road slope, reduces the operation load of the driver and the energy consumption of the vehicle, and increases the actual road endurance.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy recovery, and specifically relates to a new energy vehicle energy recovery method, system, computer and readable storage medium. Background Art

[0002] During the driving of new energy vehicles, the driver's coasting and braking operations work together to achieve the driver's deceleration intention. Most existing coasting energy recovery strategies design a fixed coasting recovery torque, and mainly achieve the driver's deceleration intention through the driver's operation of the brake pedal. During the braking deceleration process, the existing brake energy recovery system will produce a certain amount of mechanical braking energy loss: for non-decoupled brake energy recovery systems, mechanical braking is involved as soon as the brake pedal is pressed, resulting in mechanical braking energy loss; for decoupled brake energy recovery systems, mechanical braking is also involved when the pedal is pressed to a certain depth, resulting in mechanical braking energy loss. Therefore, in order to reduce the energy loss caused by mechanical braking intervention, coasting energy recovery should be fully utilized to achieve the driver's deceleration intention.

[0003] To achieve the goal of using coasting energy regeneration to meet deceleration intentions, some manufacturers increase the coasting energy regeneration intensity or design multiple coasting regeneration intensity selection gears that include strong regeneration. However, on smooth road conditions (such as highways) and uphill roads, overly strong coasting regeneration does not meet the driver's desired coasting deceleration intention under the current road conditions and will also increase energy conversion efficiency losses. Other manufacturers have designed a single-pedal mode (OnePedal) to allow the driver to control the energy regeneration intensity. However, for unskilled drivers, it is difficult to accurately control the accelerator pedal opening according to the current road conditions. Manipulating the energy regeneration intensity with a single pedal cannot accurately meet the driver's desired deceleration, resulting in a loss of energy conversion efficiency.

[0004] In summary, the existing technology has the following problems:

[0005] 1. The driver is unclear about how to select the appropriate recovery gear for the current road conditions and is unable to adapt to different road conditions and make corresponding gear adjustments;

[0006] 2. For unskilled drivers, driving comfort is poor and energy conversion efficiency is lost significantly. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a new energy vehicle energy recovery method, system, computer and readable storage medium, which are used to solve the technical problems raised in the prior art. On the basis of not changing the configuration of the existing new energy vehicle coasting energy recovery system, the target deceleration expected by the current driver can be adaptively calculated according to road congestion, slope and driving habits, and the coasting recovery torque can be accurately controlled to achieve an increase in the vehicle's cruising range of the new energy vehicle and help the driver reduce the difficulty of operation under different road conditions.

[0008] In a first aspect, an embodiment of the present invention provides the following technical solution: a method for recovering energy from a new energy vehicle, comprising:

[0009] S100: Calculating a non-slope target coasting deceleration rate based on current road condition information and the driver's deceleration driving habit data;

[0010] S200: Calculating a road slope of the vehicle on a current driving road based on the vehicle speed and longitudinal acceleration, and determining whether the current driving road is on a slope based on the road slope;

[0011] S300: If the current driving road is not on a slope, use the non-slope target coasting deceleration as the current coasting deceleration of the vehicle;

[0012] S400: If the current driving road is on a slope, calculating a target coasting deceleration on the slope according to the road slope and the vehicle speed, and using the target coasting deceleration on the slope as the current coasting deceleration of the vehicle;

[0013] S500: Calculating the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed;

[0014] S600: Calculating a coasting recovery request torque of the vehicle according to the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, and performing energy recovery according to the coasting recovery request torque of the vehicle to generate an energy recovery intensity.

[0015] Compared with the existing technology, the beneficial effects of the present application are: by obtaining the current driver's deceleration driving habit data, current road condition information and current target coasting deceleration in real time, and displaying them on the instrument panel of the new energy vehicle and through the user's mobile terminal, the user is assisted in energy-saving driving and effectively reduces fuel consumption. At the same time, without changing the configuration of the existing new energy vehicle coasting energy recovery system, the current target coasting deceleration expected by the current driver can be adaptively calculated according to the road condition, slope and driving habit, and then the target coasting recovery request torque can be accurately controlled to achieve an increase in the driving range of the new energy vehicle and help the driver reduce the difficulty of operation under different road conditions.

[0016] Preferably, the step S100 includes:

[0017] S110, obtaining an average speed, a maximum speed, and a number of stops of the vehicle in a preset historical period before a current time, and identifying current road condition information using the average speed, the maximum speed, and the number of stops;

[0018] S120: Obtaining a ratio of a coasting time to a deceleration time of the vehicle when decelerating under the current road condition information, and calculating deceleration driving habit data of the driver based on a first preset parameter and the current road condition information;

[0019] S130 , calculating the non-slope target coasting deceleration according to the current road condition information, a preset non-slope target correspondence table, and the driver's deceleration driving habit data.

[0020] Preferably, the driver's deceleration driving habit data includes the driver's deceleration driving habit score, the driver's deceleration driving habit score average, and the driving habit adjustment coefficient. The calculation formula of the driver's deceleration driving habit score is:

[0021] DrvScr=(SR_x-SR_x_min) / (SR_x_max-SR_x_min);

[0022] Wherein, DrvScr is the driver's deceleration driving habit score, SR_x is the ratio of the coasting time to the deceleration time during deceleration under the current road condition information, SR_x_min is the minimum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters, and SR_x_max is the maximum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters;

[0023] The calculation formula for the average value of the driver's deceleration driving habit score is:

[0024] DrvScr_avg=(SR_x_avg-SR_x_min) / (SR_x_max-SR_x_min);

[0025] Wherein, DrvScr_avg is the average value of the driver's deceleration driving habit score, and SR_x_avg is the average value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameter;

[0026] The calculation formula of the driving habit adjustment coefficient is:

[0027] k_DrvScr=(DrvScr_avg-DrvScr+100) / 100;

[0028] Where k_DrvScr is the driving habit adjustment coefficient.

[0029] Preferably, in step S200, the calculation formula of the road slope is:

[0030]

[0031] a=dv / dt;

[0032] Where, is the road slope, a esp is the longitudinal acceleration of the vehicle, a is the true longitudinal acceleration obtained by derivation of the vehicle speed, and v is the vehicle speed.

[0033] Preferably, in step S400, the step of calculating the target slope coasting deceleration according to the road slope and the vehicle speed includes:

[0034] The ramp target coasting deceleration is calculated according to a preset ramp target correspondence table, the road gradient and the vehicle speed.

[0035] Preferably, in step S500, the vehicle weight is calculated as follows:

[0036]

[0037] Where, T m is the real-time torque of the motor, m is the vehicle weight, g is the acceleration of gravity, f is the rolling resistance coefficient, i0 is the speed ratio of the reducer, R is the rolling radius of the tire, η is the mechanical transmission efficiency, is the road slope, C D is the drag coefficient, A is the frontal area, v is the current vehicle speed, and δ is the rotational mass conversion coefficient.

[0038] Preferably, in step S600, the calculation formula of the coasting recovery request torque of the vehicle is:

[0039]

[0040] Where T is the vehicle's coasting recovery request torque.

[0041] In a second aspect, an embodiment of the present invention provides the following technical solution: an energy recovery system for a new energy vehicle, comprising:

[0042] The first calculation module is used to calculate the non-slope target coasting deceleration based on the current road condition information and the driver's deceleration driving habit data;

[0043] a judgment module, configured to calculate the road slope of the vehicle on the current driving road according to the vehicle speed and longitudinal acceleration, and to judge whether the current driving road is a slope condition according to the road slope;

[0044] a first processing module, configured to use the non-ramp target coasting deceleration as the current coasting deceleration of the vehicle if the current driving road is not on a slope;

[0045] a second processing module, which calculates a target coasting deceleration on the slope according to the road gradient and the vehicle speed if the current driving road is on a slope, and uses the target coasting deceleration on the slope as the current coasting deceleration of the vehicle;

[0046] a second calculation module, configured to calculate the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed;

[0047] An energy recovery module is configured to calculate a coasting recovery request torque of the vehicle according to the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, and to perform energy recovery and generate an energy recovery intensity according to the coasting recovery request torque of the vehicle.

[0048] In a third aspect, an embodiment of the present invention provides the following technical solution: a computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; the processor implements the above-mentioned new energy vehicle energy recovery method when executing the computer program.

[0049] In a fourth aspect, an embodiment of the present invention provides the following technical solution: a readable storage medium having a computer program stored thereon, and the computer program, when executed by a processor, implements the above-mentioned new energy vehicle energy recovery method. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. 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 any creative work.

[0051] Figure 1 A flow chart of a new energy vehicle energy recovery method provided by an embodiment of the present invention;

[0052] Figure 2 A structural diagram of a fuzzy controller provided by an embodiment of the present invention;

[0053] Figure 3 A membership function diagram of the input and output variables of the fuzzy controller provided by an embodiment of the present invention;

[0054] Figure 4 A structural block diagram of the energy recovery system for new energy vehicles provided by an embodiment of the present invention;

[0055] Figure 5 A structural diagram of a vehicle device provided by an embodiment of the present invention;

[0056] Figure 6 A schematic diagram of the hardware structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0057] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the embodiments of the present invention, and should not be construed as limiting the present invention.

[0058] In the description of the embodiments of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the embodiments of the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention.

[0059] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of the technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0060] In the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "installed," "connected," "connected," "fixed," etc. should be understood in a broad sense. For example, they may refer to fixed connection, detachable connection, or integration; mechanical connection or electrical connection; direct connection or indirect connection through an intermediate medium; internal communication between two components or interaction between two components. Those skilled in the art will understand the specific meanings of the above terms in the embodiments of the present invention based on specific circumstances.

[0061] like Figure 1 As shown, in a first aspect, an embodiment of the present invention provides the following technical solution, a new energy vehicle energy recovery method, comprising:

[0062] S100, calculating a non-slope target coasting deceleration rate based on current road condition information and the driver's deceleration driving habit data;

[0063] In this embodiment, step S100 includes:

[0064] S110, obtaining an average speed, a maximum speed, and a number of stops of the vehicle in a preset historical period before a current time, and identifying current road condition information using the average speed, the maximum speed, and the number of stops;

[0065] The preset historical period is 30s to 60s. After obtaining the average speed, maximum speed, and number of stops of the vehicle in the preset historical period before the current time, a fuzzy control algorithm is used to output a current road condition flag using the average speed, maximum speed, and number of stops to obtain current road condition information.

[0066] It is worth noting that, in actual driving, the road condition is relatively stable in a short period of time. In layman's terms, the average speed, maximum speed, and number of stops of the vehicle obtained in the preset historical period before the current time are basically the same as the average speed, maximum speed, and number of stops of the vehicle at the current moment, and the road condition will not change drastically in a short period of time. Therefore, in this embodiment, by obtaining the average speed, maximum speed, and number of stops of the vehicle in the preset historical period, the average speed, maximum speed, and number of stops of the vehicle at the current moment can be obtained. The current road condition flag representing the road congestion situation can be output based on the average speed, maximum speed, and number of stops of the vehicle, and the current road condition information can be obtained.

[0067] The fuzzy control algorithm is used to output the current road condition flag using the average vehicle speed, the maximum vehicle speed, and the number of stops to obtain the current road condition information. The fuzzy control algorithm is further explained below:

[0068] The road condition recognition fuzzy controller adopts a two-input, single-output Mamdani structure, such as Figure 2 As shown; the two inputs are the average vehicle speed of the previous cycle and the number of stops s, the output is the road smoothness coefficient Kcyc;

[0069] The input and output of the fuzzy controller are normalized so that the domain of all input and output is 0 to 1. For the average speed, 0 means the average speed is reduced, and 1 means the average speed is high; for the number of stops, 0 means more stops, and 1 means fewer stops; for the road smoothness coefficient, 0 means more congested road conditions, and 1 means smoother road conditions;

[0070] Using Gaussian membership function, the membership functions of input and output variables are as follows Figure 3 As shown;

[0071] The fuzzy subsets of input and output are defined as follows:

[0072] {LE, ML, ME, MB, GE};

[0073] s:{LE,ME,GE};

[0074] Kcyc:{LE,ML,ME,MB,GE};

[0075] Among them, LE is smaller; ME is medium; GE is larger; ML is small to medium; MB is medium to large.

[0076] After a lot of experiments, the designed fuzzy control rules are shown in Table 1 below:

[0077] Table 1 Fuzzy rules table

[0078]

[0079] The characteristic parameters of each road condition are pre-tested, and the test data are imported into the knowledge base of the fuzzy controller for learning;

[0080] After the fuzzy controller calculates the road condition smoothness Kcyc, the corresponding road condition flag Cyc_flg can be determined according to the road condition smoothness:

[0081]

[0082] In this embodiment, based on the smoothness of the road condition, the urban road condition is counted as mark 1, the suburban road condition is counted as mark 2, and the highway road condition is counted as mark 3.

[0083] S120. Obtain a ratio of the coasting time to the deceleration time of the vehicle when decelerating under the current road condition information, and calculate the driver's deceleration driving habit data based on a first preset parameter and the current road condition information.

[0084] The first preset parameter is a maximum value, a minimum value, and an average value of the ratio of the coasting time to the deceleration time during deceleration under different preset road conditions. Before step S120, it is also necessary to obtain the driver's operation signals for the accelerator pedal and the brake pedal under the current road condition information, and obtain the ratio of the coasting time to the deceleration time during deceleration of the vehicle under the current road condition information based on the operation signals;

[0085] In this embodiment, the driver's deceleration driving habit data includes the driver's deceleration driving habit score, the driver's deceleration driving habit score average, and the driving habit adjustment coefficient;

[0086] The calculation formula for the driver's deceleration driving habit score is:

[0087] DrvScr=(SR_x-SR_x_min) / (SR_x_max-SR_x_min);

[0088] Where DrvScr is the driver's deceleration driving habit score, SR_x is the ratio of the coasting time to the deceleration time during the deceleration process under the current road condition sign, SR_x_min is the minimum value of the ratio of the coasting time to the deceleration time during the deceleration process under the same road condition sign as the current road condition sign, and SR_x_max is the maximum value of the ratio of the coasting time to the deceleration time during the deceleration process under the same road condition sign as the current road condition sign;

[0089] The driver's deceleration driving habit data includes the driver's deceleration driving habit score, the driver's deceleration driving habit score average, and the driving habit adjustment coefficient. The driver's deceleration driving habit score average is calculated as follows:

[0090] DrvScr_avg=(SR_x_avg-SR_x_min) / (SR_x_max-SR_x_min);

[0091] Where DrvScr_avg is the average value of the driver's deceleration driving habit score, and SR_x_avg is the average value of the ratio of the coasting time to the deceleration time during the deceleration process under the same road condition sign as the current road condition sign;

[0092] The driving habit adjustment coefficient calculation formula is:

[0093] k_DrvScr=(DrvScr_avg-DrvScr+100) / 100;

[0094] Where k_DrvScr is the driving habit adjustment coefficient, DrvScr_avg is the average value of the driver's deceleration driving habit score, and DrvScr is the driver's deceleration driving habit score. For example, if the driver's deceleration driving habit score is 50 and the average value of the driver's deceleration driving habit score is 20, then the driving habit adjustment coefficient is 0.7;

[0095] Among them, the above-mentioned driver's deceleration driving habit score is used to indicate the quality of the driver's deceleration driving habit. The value range of the driver's deceleration driving habit score is between 0 and 100. The higher the driver's deceleration driving habit score, the better the driver's deceleration driving habit.

[0096] The steps for obtaining the preset non-slope target correspondence table and the maximum, minimum, and average values ​​of the ratio of the coasting time to the deceleration time under different road conditions are as follows:

[0097] Comprehensive road conditions of selected routes frequently used by customers;

[0098] The comprehensive road conditions are divided into sections with different congestion levels, and characteristic parameters of different sections are counted, such as the average speed, maximum speed, and number of stops per unit time. For example:

[0099] 60s average speed Number of stops in 60 seconds Urban section 25km / h 3 Suburban section 50km / h 1 High-speed section 110km / h 0

[0100] Under different road conditions, drivers with different driving habits were selected to test the proportion of their coasting operation time during the deceleration process, and the maximum, minimum and average values ​​were recorded. For example:

[0101]

[0102] According to different road conditions, road sections with different congestion levels are decomposed from the comprehensive road conditions, and the first expected coasting deceleration is calibrated under different road sections to obtain a non-slope target correspondence table, for example:

[0103] Urban section 0.12g Suburban section 0.08g High-speed section 0.05g

[0104] S130, calculating the non-slope target coasting deceleration according to the current road condition information, a preset non-slope target correspondence table, and the driver's deceleration driving habit data;

[0105] In step S130, the non-slope target correspondence table is searched according to the current road condition information to obtain the non-slope target expected coasting deceleration table value. The non-slope target coasting deceleration calculation formula is:

[0106] A_CycX_DrvY=LookMAP(Cyc_flg_A)*k_DrvScr;

[0107] Where A_CycX_DrvY is the non-slope target coasting deceleration, and LookMAP(Cyc_flg_A) is the non-slope target desired coasting deceleration lookup table value.

[0108] S200: Calculating a road slope of the vehicle on a current driving road based on the vehicle speed and longitudinal acceleration, and determining whether the current driving road is on a slope based on the road slope;

[0109] In this embodiment, step S200 includes:

[0110] The calculation formula of the road slope is:

[0111]

[0112] a=dv / dt;

[0113] Where, is the road slope, a esp is the longitudinal acceleration of the vehicle, a is the true longitudinal acceleration obtained by derivation of the vehicle speed, and v is the vehicle speed;

[0114] The vehicle speed and longitudinal acceleration of the vehicle need to be acquired in advance, and the road slope of the current road on which the vehicle is traveling needs to be calculated based on the vehicle speed and longitudinal acceleration.

[0115] At the same time, judging whether the current driving road belongs to a ramp condition according to the road slope, when the absolute value of the road slope is greater than the slope threshold, it is judged to be a ramp condition, and when the absolute value of the road slope is not greater than the slope threshold, it is judged to be a non-ramp condition;

[0116] Specifically, the slope threshold is 4°. When the slope is greater than 4°, it is judged as a ramp condition; when the slope is ≤ 4°, it is judged as a non-ramp condition.

[0117] S300: If the current driving road is not on a slope, the non-slope target deceleration is used as the current coasting deceleration of the vehicle.

[0118] S400: If the current driving road is on a slope, calculating a target slope deceleration according to the road slope and the vehicle speed, and using the target slope deceleration as the current coasting deceleration of the vehicle;

[0119] In this embodiment, step S400 includes:

[0120] Calculating the target slope deceleration based on a preset slope target correspondence table, the road slope, and the vehicle speed;

[0121] The preset steps of the slope target relationship correspondence table are as follows: calibrating the driver's expected slope target coasting deceleration under different road slopes, for example:

[0122]

[0123] Querying the ramp target correspondence table according to the road slope to obtain a ramp target expected coasting deceleration lookup table value;

[0124] Calculate the target slope deceleration according to the slope target expected coasting deceleration table value:

[0125] B_CycX_DrvY=LookMAP(Cyc_flg_B);

[0126] Where B_CycX_DrvY is the target coasting deceleration on the ramp, and LookMAP(Cyc_flg_B) is the lookup table value of the target desired coasting deceleration on the ramp.

[0127] S500: Calculating the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed;

[0128] In this embodiment, step S500 includes:

[0129] Obtaining the real-time torque of the motor of the vehicle, and calculating the weight of the vehicle according to the vehicle speed, the longitudinal acceleration of the vehicle, and the real-time torque of the motor of the vehicle;

[0130] The calculation formula of the vehicle weight is:

[0131]

[0132] Where, T m is the real-time torque of the motor, m is the vehicle weight, g is the acceleration of gravity, f is the rolling resistance coefficient, i0 is the speed ratio of the reducer, R is the rolling radius of the tire, η is the mechanical transmission efficiency, is the road slope, C D is the drag coefficient, A is the frontal area, v is the current vehicle speed, and δ is the rotational mass conversion coefficient.

[0133] Step S600: calculating a coasting regeneration request torque of the vehicle according to the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, and performing energy recovery according to the coasting regeneration request torque of the vehicle to generate an energy recovery intensity;

[0134] In this embodiment, step S600 includes:

[0135] The calculation formula of the coasting recovery request torque of the vehicle is:

[0136]

[0137] Where T is the vehicle's coasting recovery request torque.

[0138] In this embodiment, the method further includes the following steps:

[0139] S700: Display the driver's deceleration driving habit data, the current target coasting deceleration, and the energy recovery intensity.

[0140] like Figure 4 As shown, in a second aspect, an embodiment of the present invention provides the following technical solution, a new energy vehicle energy recovery system, comprising:

[0141] The first calculation module 100 is used to calculate the non-slope target coasting deceleration based on the current road condition information and the driver's deceleration driving habit data;

[0142] A determination module 200 is configured to calculate the road slope of the vehicle on the current road based on the vehicle speed and longitudinal acceleration, and determine whether the current road is on a slope based on the road slope;

[0143] A first processing module 300 is configured to use the non-slope target coasting deceleration as the current coasting deceleration of the vehicle if the current driving road is not on a slope;

[0144] A second processing module 400 is configured to calculate a target coasting deceleration on a slope according to the road gradient and the vehicle speed if the current driving road is on a slope, and use the target coasting deceleration on a slope as the current coasting deceleration of the vehicle;

[0145] A second calculation module 500 is configured to calculate the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed;

[0146] an energy recovery module 600, configured to calculate a coasting recovery request torque of the vehicle based on the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, and to perform energy recovery based on the coasting recovery request torque of the vehicle and generate an energy recovery intensity;

[0147] Furthermore, the first calculation module 100 includes:

[0148] a first acquiring unit, configured to acquire an average speed, a maximum speed, and a number of stops of the vehicle in a preset historical period before a current time, and identify current road condition information using the average speed, the maximum speed, and the number of stops;

[0149] a second acquiring unit configured to acquire an operation signal of the driver on the accelerator pedal and the brake pedal under the current road condition information, obtain a ratio of a coasting time to a deceleration time of the vehicle during deceleration under the current road condition information based on the operation signal, and calculate deceleration driving habit data of the driver based on a maximum value, a minimum value, and an average value of the ratio of the coasting time to the deceleration time during deceleration under different preset road conditions and the current road condition information;

[0150] a first calculation unit, configured to calculate the non-slope target coasting deceleration based on the current road condition information, a preset non-slope target correspondence table, and the driver's deceleration driving habit data;

[0151] Furthermore, the second acquiring unit is further configured to:

[0152] The driver's deceleration driving habit data is calculated as follows. The driver's deceleration driving habit data includes the driver's deceleration driving habit score, the average of the driver's deceleration driving habit scores, and the driving habit adjustment coefficient. The calculation formula for the driver's deceleration driving habit score is:

[0153] DrvScr=(SR_x-SR_x_min) / (SR_x_max-SR_x_min);

[0154] Wherein, DrvScr is the driver's deceleration driving habit score, SR_x is the ratio of the coasting time to the deceleration time during deceleration under the current road condition information, SR_x_min is the minimum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters, and SR_x_max is the maximum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters;

[0155] The calculation formula for the average value of the driver's deceleration driving habit score is:

[0156] DrvScr_avg=(SR_x_avg-SR_x_min) / (SR_x_max-SR_x_min);

[0157] Wherein, DrvScr_avg is the average value of the driver's deceleration driving habit score, and SR_x_avg is the average value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameter;

[0158] The calculation formula of the driving habit adjustment coefficient is:

[0159] k_DrvScr=(DrvScr_avg-DrvScr+100) / 100;

[0160] Where, k_DrvScr is the driving habit adjustment coefficient;

[0161] Furthermore, the judgment module 200 is further configured to:

[0162] The road slope is calculated as follows:

[0163]

[0164] a=dv / dt;

[0165] Where, is the road slope, a esp is the longitudinal acceleration of the vehicle, a is the true longitudinal acceleration obtained by derivation of the vehicle speed, and v is the vehicle speed;

[0166] Furthermore, the second processing module 400 is further configured to:

[0167] Calculating the target slope deceleration based on a preset slope target correspondence table, the road slope, and the vehicle speed;

[0168] Furthermore, the second calculation module 500 is further configured to:

[0169] The vehicle weight is calculated as follows:

[0170]

[0171] Where, T m is the real-time torque of the motor, m is the vehicle weight, g is the acceleration of gravity, f is the rolling resistance coefficient, i0 is the speed ratio of the reducer, R is the rolling radius of the tire, η is the mechanical transmission efficiency, is the road slope, C D is the drag coefficient, A is the frontal area, v is the current vehicle speed, and δ is the rotational mass conversion coefficient;

[0172] Furthermore, the energy recovery module 600 is further configured to:

[0173] The coasting recovery request torque of the vehicle is calculated as follows:

[0174]

[0175] Where, T is the vehicle's coasting recovery request torque;

[0176] In this embodiment, the new energy vehicle energy recovery system further includes a display unit, which is configured to display the driver's deceleration driving habit data, the current target coasting deceleration, and the energy recovery intensity.

[0177] like Figure 5 As shown, it is worth noting that the above-mentioned new energy vehicle energy recovery system is applied to a whole vehicle device, and the whole vehicle device includes a whole vehicle controller 10 and a motor controller 30, wherein the whole vehicle controller 10 is electrically connected to a vehicle speed sensor 101, a longitudinal acceleration sensor 102, a throttle opening sensor 103, and a brake opening sensor 104;

[0178] Among them, the vehicle controller 10 and the motor controller 30 are used to control the operation of the first calculation module 100, the judgment module 200, the first processing module 300, the second processing module 400, the second processing module 500 and the energy recovery module 600;

[0179] The vehicle speed sensor 101 is used to obtain current road condition information and vehicle speed;

[0180] The longitudinal acceleration sensor 102 is used to obtain the longitudinal acceleration of the vehicle;

[0181] The throttle opening sensor 103 and the brake opening sensor 104 are used to obtain the driver's operation signals on the throttle pedal and the brake pedal;

[0182] The motor controller 30 is configured to obtain the real-time torque of the motor of the vehicle, execute the energy recovery process, and generate the energy recovery intensity.

[0183] In this embodiment, the vehicle device further includes an instrument controller 20 , and the instrument controller 20 is configured to display the driver's deceleration driving habit data, the current target coasting deceleration, and the energy recovery intensity.

[0184] In a third aspect, an embodiment of the present invention provides the following technical solution: a computer comprising a memory 42, a processor 41, and a computer program stored in the memory 42 and executable on the processor 41; the processor 41 implements the above-mentioned new energy vehicle energy recovery method when executing the computer program.

[0185] Specifically, the processor 41 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0186] Among them, the memory 42 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 42 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 42 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 42 may be inside or outside the data processing device. In a specific embodiment, the memory 42 is a non-volatile memory. In a specific embodiment, the memory 42 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically alterable ROM (EAROM) or a flash memory (FLASH), or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), where the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0187] The memory 42 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 41 .

[0188] The processor 41 implements the above-mentioned new energy vehicle energy recovery method by reading and executing computer program instructions stored in the memory 42.

[0189] In some embodiments, the computer may further include a communication interface 43 and a bus 40. Figure 6 As shown, the processor 41 , the memory 42 , and the communication interface 43 are connected via a bus 40 and communicate with each other.

[0190] The communication interface 43 is used to implement communication between the various modules, devices, units, and / or devices in the embodiments of the present application. The communication interface 43 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0191] The bus 40 includes hardware, software, or both, and couples the components of the computer device to each other. The bus 40 includes, but is not limited to, at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 40 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of the above. Bus 40 may include one or more buses, where appropriate. Although embodiments herein describe and illustrate a particular bus, this application contemplates any suitable bus or interconnect.

[0192] The computer can execute the new energy vehicle energy recovery method of the present application based on the acquired new energy vehicle energy recovery system, thereby realizing energy recovery.

[0193] In the fourth aspect, in combination with the above-mentioned new energy vehicle energy recovery method, an embodiment of the present invention provides the following technical solution: a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned new energy vehicle energy recovery method is implemented.

[0194] Those skilled in the art will appreciate that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0195] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0196] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement the hardware: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0197] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0198] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A new energy vehicle energy recovery method, characterized in that: include: S100: Calculating a non-slope target coasting deceleration rate based on current road condition information and the driver's deceleration driving habit data; S200: Calculating a road slope of the vehicle on a current driving road based on the vehicle speed and longitudinal acceleration, and determining whether the current driving road is on a slope based on the road slope; S300: If the current driving road is not on a slope, use the non-slope target coasting deceleration as the current coasting deceleration of the vehicle; S400: If the current driving road is on a slope, calculating a target coasting deceleration on the slope according to the road slope and the vehicle speed, and using the target coasting deceleration on the slope as the current coasting deceleration of the vehicle; S500: Calculating the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed; S600: calculating a coasting regeneration request torque of the vehicle according to the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, performing energy recovery according to the coasting regeneration request torque of the vehicle and generating an energy recovery intensity; The step S100 includes: S110, obtaining an average speed, a maximum speed, and a number of stops of the vehicle in a preset historical period before a current time, and identifying current road condition information using the average speed, the maximum speed, and the number of stops; S120: Obtaining a ratio of a coasting time to a deceleration time of the vehicle when decelerating under the current road condition information, and calculating deceleration driving habit data of the driver based on a first preset parameter and the current road condition information; S130, calculating the non-slope target coasting deceleration according to the current road condition information, a preset non-slope target correspondence table, and the driver's deceleration driving habit data; The driver's deceleration driving habit data includes the driver's deceleration driving habit score, the driver's deceleration driving habit score average, and the driving habit adjustment coefficient. The calculation formula of the driver's deceleration driving habit score is: DrvScr=(SR_x-SR_x_min) / (SR_x_max-SR_x_min); Wherein, DrvScr is the driver's deceleration driving habit score, SR_x is the ratio of the coasting time to the deceleration time during deceleration under the current road condition information, SR_x_min is the minimum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters, and SR_x_max is the maximum value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameters; The calculation formula for the average value of the driver's deceleration driving habit score is: DrvScr_avg=(SR_x_avg-SR_x_min) / (SR_x_max-SR_x_min); Wherein, DrvScr_avg is the average value of the driver's deceleration driving habit score, and SR_x_avg is the average value of the ratio of the coasting time to the deceleration time during deceleration under the current road condition information in the first preset parameter; The calculation formula of the driving habit adjustment coefficient is: k_DrvScr=(DrvScr_avg-DrvScr+100) / 100; Where k_DrvScr is the driving habit adjustment coefficient.

2. The new energy vehicle energy recovery method according to claim 1, characterized in that: In step S200, the calculation formula of the road slope is: β=arcsin[(a esp -branch]; a=dv / dt; Where β is the road slope, a esp is the longitudinal acceleration of the vehicle, a is the true longitudinal acceleration obtained by derivation of the vehicle speed, and v is the vehicle speed.

3. The new energy vehicle energy recovery method according to claim 2, characterized in that: In step S500, the vehicle weight is calculated as follows: Where, T m is the real-time torque of the motor, m is the vehicle weight, g is the acceleration of gravity, f is the rolling resistance coefficient, i0 is the speed ratio of the reducer, R is the tire rolling radius, η is the mechanical transmission efficiency, β is the road slope, C D is the drag coefficient, A is the frontal area, v is the current vehicle speed, and δ is the rotational mass conversion coefficient.

4. The energy recovery method for new energy vehicles according to claim 3, characterized in that: In step S600, the calculation formula of the coasting recovery request torque of the vehicle is: Where T is the vehicle's coasting recovery request torque.

5. A new energy vehicle energy recovery system, the system adopts the new energy vehicle energy recovery method as claimed in claim 1, characterized in that: include: The first calculation module is used to calculate the non-slope target coasting deceleration based on the current road condition information and the driver's deceleration driving habit data; a judgment module, configured to calculate the road slope of the vehicle on the current driving road according to the vehicle speed and longitudinal acceleration, and to judge whether the current driving road is a slope condition according to the road slope; a first processing module, configured to use the non-ramp target coasting deceleration as the current coasting deceleration of the vehicle if the current driving road is not on a slope; a second processing module, which calculates a target coasting deceleration on the slope according to the road gradient and the vehicle speed if the current driving road is on a slope, and uses the target coasting deceleration on the slope as the current coasting deceleration of the vehicle; a second calculation module, configured to calculate the vehicle weight according to the real-time torque of the motor of the vehicle, the road slope, and the vehicle speed; An energy recovery module is configured to calculate a coasting recovery request torque of the vehicle according to the current coasting deceleration of the vehicle, the road gradient, and the vehicle weight, and to perform energy recovery and generate an energy recovery intensity according to the coasting recovery request torque of the vehicle.

6. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the new energy vehicle energy recovery method according to any one of claims 1 to 4 is implemented.

7. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the new energy vehicle energy recovery method according to any one of claims 1 to 4 is implemented.

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