Electric energy recovery method, system and storage medium for electric bicycle

Abstract

The embodiments of the present application relate to the field of electric energy recovery technology, and disclose an electric energy recovery method, system, and storage medium for an electric bicycle. The electric energy recovery method for an electric bicycle of the present application determines the risk factor of the vehicle by identifying obstacles ahead, and corrects the risk factor in combination with the obstacle-crossing performance of the electric bicycle to obtain a target risk factor. When the target risk factor is large, emergency braking is performed, and electric energy recovery in the first state is performed during the emergency braking process. When the target risk factor is small, preventive braking is performed, and electric energy recovery in the second state is performed during the preventive braking process. In this way, during the active obstacle avoidance braking process, electric energy recovery in different states is performed according to the different degrees of danger of the electric bicycle, thereby avoiding the reduction of the endurance of the electric bicycle due to the extra loss of electric energy during the active obstacle avoidance process. The electric energy recovery method is relatively flexible and meets the actual needs of users.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy recovery, and in particular to an electric energy recovery method, system and storage medium for an electric bicycle. Background Art

[0002] As an important part of modern transportation, electric bicycles are favored by consumers for their environmental protection, energy saving, convenience and other characteristics. During riding, electric bicycles not only provide power support for riders, but are also often equipped with active obstacle avoidance systems to improve riding safety. However, in the actual application of electric bicycle active obstacle avoidance technology, there are still some technical problems that need to be solved.

[0003] Specifically, when an electric bicycle actively avoids obstacles, the obstacle avoidance assist component will respond quickly and start to assist the rider in avoiding obstacles. However, during this process, the obstacle avoidance assist component consumes a certain amount of electrical energy, resulting in a loss of overall electrical energy in the electric bicycle. This electrical energy loss will affect the endurance of the electric bicycle and reduce the mileage when fully charged, thus having a certain impact on the user.

[0004] In the related art, the energy recovery method only considers the vehicle's driving speed or acceleration and the distance between the vehicle and the obstacle to control energy recovery. For example, the Chinese patent application with application number 202311487931.4 has poor flexibility in energy recovery and cannot meet the actual needs of electric bicycle drivers. Summary of the invention

[0005] The main purpose of the present invention is to provide an electric energy recovery method, system and storage medium for an electric bicycle, aiming to solve the technical problem that the electric energy recovery in the prior art has poor flexibility and cannot meet the actual needs of users.

[0006] To achieve the above-mentioned purpose, in a first aspect, an embodiment of the present application provides an electric energy recovery method for an electric bicycle, which is applied to an electric energy recovery system, wherein the electric energy recovery system includes an obstacle detection device and an electric energy recovery device, wherein the electric energy recovery device includes a drive motor for driving the electric bicycle, an electric energy recovery control circuit and an energy storage battery, and the method includes:

[0007] Obtain target obstacle information located in front of the vehicle during the driving of the electric bicycle;

[0008] Determine the danger factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle;

[0009] Obtaining obstacle-crossing related parameters of the electric bicycle, wherein the obstacle-crossing related parameters include tire width, drive motor power, and suspension system shock absorption level;

[0010] Correcting the risk factor according to the obstacle-crossing associated parameters of the electric bicycle and the target obstacle information to obtain a target risk factor;

[0011] Determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle, wherein the obstacle avoidance type includes one of emergency obstacle avoidance and preventive obstacle avoidance;

[0012] When it is determined that the obstacle avoidance type to be initiated by the vehicle is emergency obstacle avoidance, the energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to perform braking at a first acceleration to perform electric energy recovery in a first state.

[0013] In a possible implementation, after determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle, the method further includes:

[0014] When it is determined that the obstacle avoidance type that the vehicle needs to initiate is preventive obstacle avoidance, the energy recovery circuit is turned on and the drive motor of the electric bicycle is controlled to perform braking at a second acceleration to perform electric energy recovery in a second state, wherein the second acceleration is less than the first acceleration.

[0015] In a possible implementation, turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to perform braking at a first acceleration to recover electric energy in a first state includes:

[0016] Turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to brake and decelerate with a first braking current to recover electric energy in a first state; and / or,

[0017] The method of turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to perform braking at a second acceleration to recover electric energy in a second state includes:

[0018] The energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to brake and decelerate with a second braking current to perform electric energy recovery in a second state, wherein the first braking current is greater than the first braking current.

[0019] In a possible implementation, the obstacle detection device includes a camera and an infrared sensor, the target obstacle information includes distance information between the electric bicycle and the target obstacle and size information of the target obstacle, and the step of obtaining the target obstacle information located in front of the electric bicycle during its travel includes:

[0020] Acquiring size information of a target obstacle located in front of the electric bicycle during its travel based on the target obstacle image captured by the camera; and

[0021] The distance information between the electric bicycle and the target obstacle is obtained based on the infrared sensor.

[0022] In a possible implementation, the size information of the target obstacle includes length size information of the target obstacle, and determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes:

[0023] Obtain a relationship mapping table between obstacle length, vehicle speed and vehicle risk factor;

[0024] The relationship mapping table is queried according to the length of the target obstacle and the current speed of the vehicle to determine the danger factor of the electric bicycle.

[0025] In a possible implementation, the size information of the target obstacle includes height size information of the target obstacle, and determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes:

[0026] Obtain a relationship mapping table between obstacle height, vehicle speed and vehicle risk factor;

[0027] The relationship mapping table is queried according to the height size of the target obstacle and the current speed of the vehicle to determine the danger factor of the electric bicycle.

[0028] In a possible implementation, the step of correcting the risk factor according to the obstacle-crossing associated parameter of the electric bicycle and the target obstacle information to obtain a target risk factor includes:

[0029] Determining a quantitative evaluation value of obstacle crossing performance according to obstacle crossing associated parameters of the electric bicycle;

[0030] Determining an obstacle force evaluation value of the target obstacle according to the target obstacle information;

[0031] Correcting the risk factor according to the quantified evaluation value of the obstacle crossing performance of the electric bicycle and the obstacle force evaluation value of the target obstacle to obtain a target risk factor;

[0032] Among them, when the quantitative evaluation value of the obstacle crossing performance of the electric bicycle is greater than or equal to the obstacle force evaluation value of the target obstacle, the risk factor is reversely corrected to reduce the target risk factor; when the quantitative evaluation value of the obstacle crossing performance of the electric bicycle is less than the obstacle force evaluation value of the target obstacle, the risk factor is positively corrected to increase the target risk factor.

[0033] In a possible implementation, determining the obstacle crossing performance quantitative evaluation value according to the obstacle crossing associated parameter of the electric bicycle includes:

[0034] The obstacle-crossing associated parameters of the electric bicycle are input into the obstacle-crossing performance quantitative prediction model to obtain the obstacle-crossing performance quantitative evaluation value, wherein the obstacle-crossing performance quantitative prediction model satisfies the following expression:

[0035]

[0036] Where W is the front wheel width of the electric bicycle, W 0 is the reference front wheel width, Y 1 is the quantitative evaluation value of the benchmark obstacle crossing performance under the benchmark front wheel width, P is the driving motor power, P 0 is the base power of the drive motor, Y 2 is the quantitative evaluation value of the benchmark obstacle crossing performance under the benchmark power of the driving motor, Y 3 Y is the quantitative evaluation value of obstacle crossing performance when the shock absorption level of the suspension system is greater than or equal to 3. 4 is the quantitative evaluation value of obstacle crossing performance when the shock absorption level of the suspension system is less than 3, N is the shock absorption level of the suspension system, θ 1 ,θ 2 ,θ 3 are the corresponding influence weights respectively.

[0037] In a possible implementation, determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle includes:

[0038] If the target risk factor of the electric bicycle is greater than or equal to the risk factor threshold, determining that the obstacle avoidance type to be activated is emergency obstacle avoidance;

[0039] If the target risk factor of the electric bicycle is less than the risk factor threshold, it is determined that the obstacle avoidance type to be activated is preventive obstacle avoidance.

[0040] In a second aspect, an embodiment of the present application further provides an electric energy recovery system, comprising:

[0041] An obstacle detection device, the obstacle detection device comprising a camera and an infrared sensor;

[0042] An electric energy recovery device, the electric energy recovery device comprising a driving motor for driving an electric bicycle, an electric energy recovery control circuit and an energy storage battery;

[0043] a memory for storing program code; and

[0044] A processor, wherein the processor is used to call the program code to execute the method as described in the first aspect.

[0045] In a third aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0046] Different from the prior art, the electric energy recovery method of the electric bicycle provided in the embodiment of the present application first obtains the target obstacle information located in front of the vehicle during the driving process of the electric bicycle; then determines the danger coefficient of the electric bicycle according to the target obstacle information and the current speed of the vehicle; then obtains the obstacle crossing associated parameters of the electric bicycle; then corrects the danger coefficient according to the obstacle crossing associated parameters of the electric bicycle and the target obstacle information to obtain the target danger coefficient; then determines the obstacle avoidance type to be activated according to the target danger coefficient of the electric bicycle; when it is determined that the obstacle avoidance type to be activated by the vehicle is emergency obstacle avoidance, turns on the energy recovery circuit and controls the driving motor of the electric bicycle to perform the first acceleration braking to perform the first state of electric energy recovery. That is, the danger coefficient of the vehicle driving is determined by the front obstacle recognition, and the danger coefficient is corrected to obtain the target danger coefficient in combination with the obstacle crossing performance of the electric bicycle, emergency braking is performed when the target danger coefficient is large, and the electric energy recovery of the first state is performed during the emergency braking process, and preventive braking is performed when the target danger coefficient is small, and the electric energy recovery of the second state is performed during the preventive braking process. In this way, during the active obstacle avoidance braking process, different states of electric energy recovery are performed according to the different degrees of danger of the electric bicycle, thereby avoiding additional energy loss during the active obstacle avoidance process and reducing the endurance of the electric bicycle. The energy recovery method is more flexible and meets the actual needs of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] 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 or the description of the prior art 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 the structures shown in these drawings without paying creative work.

[0048] Figure 1 This is a schematic diagram of the power supply and energy storage process of an electric bicycle in some embodiments of the present application;

[0049] Figure 2 A schematic diagram of a flow chart of a method for recovering electric energy of an electric bicycle in some embodiments of the present application;

[0050] Figure 3 A schematic diagram of a flow chart of an electric energy recovery method for an electric bicycle in some other embodiments of the present application;

[0051] Figure 4 This is a schematic diagram of the hardware structure of the electric energy recovery system in some embodiments of the present application.

[0052] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] It should be noted that all directional indications in the embodiments of the present invention (such as up, down, left, right, front, back, etc.) are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0055] In addition, the descriptions of "first", "second", etc. in the present invention are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in this field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0056] As an important part of modern transportation, electric bicycles are favored by consumers for their environmental protection, energy saving, convenience and other characteristics. During riding, electric bicycles not only provide power support for riders, but are also often equipped with active obstacle avoidance systems to improve riding safety. However, in the actual application of electric bicycle active obstacle avoidance technology, there are still some technical problems that need to be solved.

[0057] Specifically, when an electric bicycle actively avoids obstacles, the obstacle avoidance assist component will respond quickly and start to assist the rider in avoiding obstacles. However, during this process, the obstacle avoidance assist component consumes a certain amount of electrical energy, resulting in a loss of overall electrical energy in the electric bicycle. This electrical energy loss will affect the endurance of the electric bicycle and reduce the mileage when fully charged, thus having a certain impact on the user.

[0058] Exemplarily, the obstacle avoidance assist component may include an active braking component and an active steering component. When the vehicle encounters an obstacle, the electric bicycle will take certain obstacle avoidance measures according to the dangerous state, such as controlling the active braking component or controlling the active steering component to actively adjust the driving direction.

[0059] In the related art, the energy recovery method only considers the vehicle's speed or acceleration and the distance between the vehicle and the obstacle to control energy recovery. For example, the Chinese patent application with application number 202311487931.4 has poor flexibility in energy recovery and cannot meet the actual needs of electric bicycle drivers.

[0060] In response to the above problems, the present application proposes an energy recovery method for an electric bicycle, which is applied to an energy recovery system. The energy recovery system includes an obstacle detection device and an energy recovery device. The obstacle detection device includes a camera and an infrared sensor; the energy recovery device includes a drive motor for driving the electric bicycle, an energy recovery control circuit and a storage battery.

[0061] In one embodiment, if Figure 1 As shown, the electric bicycle of the present application includes a driving motor 100, a motor driving control circuit 200, an energy recovery control circuit 300 and an energy storage battery 400. When the electric bicycle is in normal working state, the energy recovery control circuit 300 is disconnected, and the energy storage battery 400 supplies power to the driving motor 100 through the motor driving control circuit 200; when the electric bicycle is in the energy recovery state, the motor driving control circuit 200 is disconnected, and the electric energy generated by the driving motor 100 is stored in the energy storage battery 400 through the energy recovery control circuit 300.

[0062] The principle of energy recovery in electric bicycles is that the kinetic energy generated by the rotor of the driving motor during deceleration is converted into electrical energy (electromotive force), and the converted electrical energy is stored in the energy storage battery.

[0063] The general idea of ​​the electric energy recovery method of the electric bicycle of the present application is: determine the risk factor of the vehicle through information such as obstacle information, vehicle status information and vehicle obstacle crossing ability, select obstacle avoidance method according to the risk factor, when the risk factor is large, adopt emergency obstacle avoidance method and perform first state electric energy recovery during emergency obstacle avoidance, when the risk factor is small, adopt preventive obstacle avoidance method and perform second state electric energy recovery during preventive obstacle avoidance. The obstacle avoidance process can not only ensure driving safety, but also recover a certain amount of electric energy and improve the endurance of the electric bicycle. Since the electric energy recovery process in different states has different effects on the driving experience, the technical solution accurately obtains the risk factor of the vehicle according to information such as obstacle information, vehicle status information and vehicle obstacle crossing ability, so as to perform different degrees of electric energy recovery. For example, when the risk factor of the vehicle is high, emergency braking and first state electric energy recovery are performed, which sacrifices the driving experience while ensuring driving safety; and when the risk factor of the vehicle is low, moderate braking and second state electric energy recovery are performed, which can ensure user safety without sacrificing driving experience and meet the actual needs of users.

[0064] It should be noted that since energy recovery requires a larger braking current (or braking acceleration), that is, a larger braking acceleration can achieve a higher energy recovery efficiency, and a larger braking acceleration will bring a poor driving experience to the user. Therefore, in the technical solution of this application, the braking of the electric bicycle when it does not encounter an obstacle does not recover energy, and energy recovery is only performed when encountering an obstacle. In this way, the energy recovery process will not additionally affect the driving experience of the electric bicycle during driving.

[0065] like Figure 1-3 As shown, the following will mainly describe the specific steps of the electric energy recovery method of the electric bicycle. It should be noted that although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from here. Figure 2 , the method comprises the following steps:

[0066] S100, obtaining target obstacle information located in front of the electric bicycle during its travel;

[0067] The target obstacle of the present application refers to a ground obstacle. When the target obstacle on the ground is too large, the electric bicycle cannot cross it and the risk factor is relatively high. When the target obstacle on the ground is too small, the electric bicycle can cross it and the risk factor is relatively small.

[0068] Therefore, information such as the size of the obstacle will affect the execution of the action of the active obstacle avoidance system of the electric bicycle. Therefore, it is first necessary to know the target obstacle information located in front of the vehicle during the driving of the electric bicycle.

[0069] In one embodiment, the target obstacle information includes distance information between the electric bicycle and the target obstacle and size information of the target obstacle. The size information of the target obstacle may include height size information of the target obstacle and / or length size information of the target obstacle.

[0070] In one embodiment, the step S100: obtaining target obstacle information located in front of the electric bicycle during its travel includes:

[0071] S110, acquiring size information of a target obstacle located in front of the electric bicycle during its travel based on the target obstacle image captured by the camera; and

[0072] S120. Acquire distance information between the electric bicycle and the target obstacle based on the infrared sensor.

[0073] Specifically, an image analysis algorithm is used to analyze the target obstacle image captured by the camera to obtain the target obstacle size information, such as the height, width or length of the target obstacle. The infrared sensor can measure the distance between the electric bicycle and the target obstacle by detecting infrared radiation.

[0074] S200, determining a risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle;

[0075] It can be understood that the size of the target obstacle and the current speed of the electric bicycle will affect the driving safety of the vehicle. Therefore, the risk factor of the electric bicycle can be determined based on the target obstacle information and the current speed of the vehicle.

[0076] In one embodiment, the size information of the target obstacle includes the length size information of the target obstacle, and the step S200: determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes:

[0077] S210, obtaining a relationship mapping table between obstacle length, vehicle speed and vehicle risk factor;

[0078] S220, querying the relationship mapping table according to the length of the target obstacle and the current speed of the vehicle to determine the danger factor of the electric bicycle.

[0079] Specifically, first, a first relationship mapping table is constructed based on historical big data. Under the first relationship mapping table, the vehicle risk factor is affected by two factors: the length of the obstacle and the speed of the vehicle. Then, the risk factor of the electric bicycle is determined by querying the relationship mapping table based on the length of the target obstacle and the current speed of the vehicle. The construction process of the relationship mapping table is not an invention improvement of the present application and will not be described in detail here.

[0080] In another embodiment, the size information of the target obstacle includes height size information of the target obstacle, and the step S200: determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes:

[0081] S230, obtaining a relationship mapping table between obstacle height, vehicle speed and vehicle risk factor;

[0082] S240: Query the relationship mapping table according to the height of the target obstacle and the current speed of the vehicle to determine the risk factor of the electric bicycle.

[0083] Specifically, first, a second relationship mapping table is constructed based on historical big data. Under the second relationship mapping table, the vehicle risk factor is affected by two factors: the height size of the obstacle and the speed of the vehicle. Then, the risk factor of the electric bicycle is determined by querying the relationship mapping table based on the height size of the target obstacle and the current speed of the vehicle. Similarly, the construction process of the relationship mapping table is not an invention improvement of the present application and will not be described in detail here.

[0084] S300, obtaining obstacle-crossing related parameters of the electric bicycle, wherein the obstacle-crossing related parameters include tire width, driving motor power, and suspension system shock absorption level;

[0085] Since the electric bicycle danger factor determined above only refers to two factors: the target obstacle information and the vehicle's current speed, the accuracy of the acquired value is low. In order to improve the actual danger factor of the vehicle during driving when encountering obstacles, the initially obtained danger factor needs to be corrected.

[0086] There are many means of correction, that is, there are many factors to refer to during correction. For example, correction can be made based on the obstacle crossing performance of the electric bicycle. When the obstacle crossing performance of the electric bicycle is strong, the electric bicycle can easily cross the obstacle with the driving operation of the driving user (such as lightly lifting the handlebars when encountering an obstacle), which means that the risk factor of the vehicle is relatively low, and the estimate of the risk factor can be reduced. When the obstacle crossing performance of the electric bicycle is poor, it means that the risk factor of the vehicle is high, and the estimate of the risk factor can be increased.

[0087] The obstacle crossing performance of an electric bicycle refers to its ability to overcome obstacles. The obstacle crossing performance of an electric bicycle can be determined by obstacle crossing related parameters, for example, by one or more parameters of tire width, drive motor power, and suspension system shock absorption level.

[0088] Information such as tire width, drive motor power, and suspension system shock absorption level can be pre-stored in the memory and directly retrieved from the memory when needed.

[0089] S400, correcting the risk factor according to the obstacle crossing associated parameter of the electric bicycle and the target obstacle information to obtain a target risk factor;

[0090] It can be understood that when the electric bicycle has a strong obstacle crossing performance, even if it encounters an obstacle, the degree of danger of its driving is reduced accordingly. Therefore, the risk factor can be corrected according to the obstacle crossing associated parameters of the electric bicycle and the target obstacle information to obtain a target risk factor.

[0091] In one embodiment, the step S400: correcting the risk factor according to the obstacle-crossing associated parameter of the electric bicycle and the target obstacle information to obtain a target risk factor includes:

[0092] S410, determining a quantitative evaluation value of obstacle crossing performance according to obstacle crossing associated parameters of the electric bicycle;

[0093] S420, determining an obstacle force evaluation value of the target obstacle according to the target obstacle information;

[0094] S430, correcting the risk factor according to the quantified evaluation value of the obstacle crossing performance of the electric bicycle and the obstacle force evaluation value of the target obstacle to obtain a target risk factor;

[0095] Specifically, the obstacle crossing associated parameters of the electric bicycle can be input into the pre-trained obstacle crossing performance quantitative estimation model to obtain the obstacle crossing performance quantitative evaluation value, and the target obstacle information can be input into the pre-trained obstacle force estimation model to obtain the obstacle force evaluation value of the target obstacle. When the obstacle crossing performance quantitative evaluation value of the electric bicycle is greater than or equal to the obstacle force evaluation value of the target obstacle, it means that the obstacle crossing performance of the electric bicycle can easily deal with the target obstacle, and the degree of danger is relatively small. At this time, the danger factor is reversely corrected to reduce the target danger factor; when the obstacle crossing performance quantitative evaluation value of the electric bicycle is less than the obstacle force evaluation value of the target obstacle, it means that the obstacle crossing performance of the electric bicycle is difficult to cross the target obstacle, and the degree of danger is high. At this time, the danger factor is positively corrected to increase the target danger factor. And the greater the difference between the obstacle crossing performance quantitative evaluation value of the electric bicycle and the obstacle force evaluation value of the target obstacle, the greater the correction amount. In this way, the accuracy of the calculation of the danger factor of the electric bicycle when facing an obstacle can be improved.

[0096] It should be noted that the obstacle force estimation model of the obstacle is trained based on the magnitude of the impact of the obstacle's height and other parameters on the vehicle. Its training standard is the same as the training standard of the obstacle crossing performance quantitative estimation model, so as to facilitate the comparison between the obstacle crossing performance quantitative evaluation value and the obstacle force evaluation value of the target obstacle.

[0097] In one embodiment, the step S410: determining the obstacle crossing performance quantitative evaluation value according to the obstacle crossing associated parameters of the electric bicycle includes:

[0098] S411, inputting the obstacle-crossing related parameters of the electric bicycle into an obstacle-crossing performance quantitative prediction model to obtain an obstacle-crossing performance quantitative evaluation value, wherein the obstacle-crossing performance quantitative prediction model satisfies the following expression:

[0099]

[0100] Where W is the front wheel width of the electric bicycle, W 0 is the reference front wheel width, Y 1 is the quantitative evaluation value of the benchmark obstacle crossing performance under the benchmark front wheel width, P is the driving motor power, P 0 is the base power of the drive motor, Y 2 is the quantitative evaluation value of the benchmark obstacle crossing performance under the benchmark power of the driving motor, Y 3 Y is the quantitative evaluation value of obstacle crossing performance when the shock absorption level of the suspension system is greater than or equal to 3. 4 is the quantitative evaluation value of obstacle crossing performance when the shock absorption level of the suspension system is less than 3, N is the shock absorption level of the suspension system, θ 1 ,θ 2 ,θ 3 are the corresponding influence weights respectively.

[0101] Specifically, the front wheel width, the driving motor power and the shock absorption level of the suspension system of the electric bicycle have a relatively large impact on the obstacle crossing performance of the vehicle. In the embodiment of the present application, the reference obstacle crossing performance quantitative evaluation value Y is obtained under the reference front wheel width. 1 , the benchmark obstacle crossing performance quantitative evaluation value Y is obtained under the benchmark motor power 2 , the corresponding level of obstacle crossing performance quantitative evaluation value Y is obtained under different suspension system shock absorption levels 3 , Y 4 Then, according to the weights of the influence of different factors on the vehicle's obstacle crossing performance, a weighted calculation is performed to obtain a quantitative evaluation value of the obstacle crossing performance under comprehensive performance; in this way, the vehicle's obstacle crossing performance is quantified through a variety of influencing factors, which is convenient for comparison with the obstacle force evaluation value of the target obstacle.

[0102] It should be noted that the obstacle crossing performance quantitative evaluation value can be obtained by querying the suspension system shock absorption level in the mapping table. The higher the suspension system shock absorption level, the stronger the obstacle crossing performance of the vehicle, and the higher the corresponding obstacle crossing performance quantitative evaluation value. Therefore, Y 3 >Y 4 .

[0103] In the process of constructing the quantitative estimation model of obstacle crossing performance, the inventor defined the reference front wheel width as 150mm, the reference obstacle crossing performance quantitative evaluation value under the reference front wheel width as 100, defined the reference power of the drive motor as 450w, the reference obstacle crossing performance quantitative evaluation value under the reference power of the drive motor as 100, defined the obstacle crossing performance quantitative evaluation value when the suspension system shock absorption level is greater than or equal to 3 as 120, and the obstacle crossing performance quantitative evaluation value when the suspension system shock absorption level is less than 3 as 90; and the inventor concluded through a large number of comparative tests that the weight of the front wheel width on the vehicle obstacle crossing performance is 0.3, the weight of the drive motor power on the vehicle obstacle crossing performance is 0.4, and the weight of the suspension system shock absorption level on the vehicle obstacle crossing performance is 0.3. Therefore, the reference obstacle crossing performance quantitative evaluation value of the electric bicycle is 106 (N is 3).

[0104] When constructing an obstacle force estimation model for obstacles, the inventors tested and found that the maximum height of the obstacle that can be safely crossed is 90 mm when the baseline front wheel width is 150 mm, the baseline power of the drive motor is 450 w, and the shock absorption level of the suspension system is 3. Therefore, the obstacle force evaluation value of the obstacle when the obstacle height is 90 mm is defined as 106, and the height of the obstacle is linearly positively correlated with the obstacle force evaluation value.

[0105] Therefore, in one embodiment, when the front wheel width of the electric bicycle is 180 mm, the drive motor power is 600 W, and the suspension system shock absorption level is 4, the obstacle crossing performance quantitative evaluation value calculated according to the above-mentioned obstacle crossing performance quantitative estimation model is 125; if the obstacle height is 90 mm at this time, since the obstacle crossing performance quantitative evaluation value (125) is greater than the obstacle force evaluation value (106) of the obstacle, it means that the electric bicycle can easily cross the target obstacle, thereby reducing the estimated value of the risk factor.

[0106] S500, determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle, wherein the obstacle avoidance type includes one of emergency obstacle avoidance and preventive obstacle avoidance;

[0107] It can be understood that when the target risk factor of the electric bicycle is high according to the obstacle information and the vehicle state, it means that urgent obstacle avoidance measures need to be taken, such as emergency braking to prevent danger from occurring;

[0108] When it is judged that the target risk factor of the electric bicycle is low based on the obstacle information and the vehicle status, it means that the electric bicycle is confident of crossing the target obstacle. At this time, there is no need to take emergency obstacle avoidance measures, but preventive obstacle avoidance measures are needed, such as performing light braking to appropriately reduce the speed (reminding the user to hold the steering control handle tightly). In this way, while ensuring safety, using light braking instead of emergency braking can improve the user's driving experience and meet the user's real needs.

[0109] When it is determined based on the obstacle information and the vehicle status that the risk factor of the electric bicycle is very low and there is almost no danger, there is no need to perform any braking operation.

[0110] S600: When it is determined that the obstacle avoidance type to be initiated by the vehicle is emergency obstacle avoidance, the energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to perform braking at a first acceleration to recover electric energy in a first state.

[0111] Specifically, when it is determined that the obstacle avoidance type to be initiated by the vehicle is emergency obstacle avoidance, that is, the vehicle needs emergency braking, the energy recovery circuit is turned on and the drive motor of the electric bicycle is controlled to perform a first acceleration braking to perform electric energy recovery in the first state (the drive motor enters the generator mode), and during the energy recovery process, the braking current in the energy recovery circuit is controlled to be larger (the first braking current). When the braking current is larger, the vehicle decelerates faster and recovers more electric energy, thereby realizing electric energy recovery in the first state (more electric energy recovery); and during the electric energy recovery process in the first state, the current in the stator coil of the drive motor forms a larger reverse torque on the rotor, thereby forming a larger braking force for emergency braking.

[0112] S700. When it is determined that the obstacle avoidance type that the vehicle needs to initiate is preventive obstacle avoidance, turn on the energy recovery circuit and control the drive motor of the electric bicycle to perform braking at a second acceleration to recover electric energy in a second state, wherein the second acceleration is less than the first acceleration.

[0113] Specifically, when it is determined that the obstacle avoidance type to be initiated by the vehicle is preventive obstacle avoidance, that is, the vehicle does not need emergency braking, but only needs slow braking to prevent potential risks in advance, the energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to brake at the second acceleration to recover the electric energy in the second state (the driving motor enters the generator mode), and the braking current in the energy recovery circuit is controlled to be smaller (the second braking current) during the energy recovery process. When the braking current is smaller, the vehicle decelerates slower, and the recovered electric energy is less, thereby realizing the electric energy recovery in the second state (less electric energy recovery); and during the electric energy recovery process in the second state, the current in the stator coil of the driving motor forms a smaller reverse torque on the rotor, thereby forming a smaller braking force for slow braking. Although the electric energy recovered in this process is less, the impact on the user's driving experience is also less, which can meet the actual needs of the user.

[0114] It can be understood that when the current in the energy recovery circuit is larger, the reverse torque of the motor stator coil on the rotor is larger, thereby making the deceleration acceleration of the drive motor larger.

[0115] It should be noted that the magnitude of the braking current in the energy recovery circuit can be controlled by the resistance value of the resistor in the energy recovery circuit.

[0116] Based on this, the electric energy recovery method of the electric bicycle of the present application determines the risk factor of the vehicle through the front obstacle recognition, and corrects the risk factor in combination with the obstacle crossing performance of the electric bicycle to obtain the target risk factor. When the target risk factor is large, emergency braking is performed, and the first state of electric energy recovery is performed during the emergency braking process. When the target risk factor is small, preventive braking is performed, and the second state of electric energy recovery is performed during the preventive braking process. In this way, when the vehicle risk factor is high, emergency braking and first state of electric energy recovery are performed, which sacrifices the driving experience while ensuring driving safety; and when the vehicle risk factor is low, moderate braking and second state of electric energy recovery are performed, which can ensure the safety of users without sacrificing the driving experience. The electric energy recovery method is more flexible, which can not only meet the actual needs of users, but also avoid the additional loss of electric energy during active obstacle avoidance and reduce the endurance of the electric bicycle.

[0117] The embodiment of the present application provides an electric energy recovery system, which also includes a memory 110 and a processor 120, wherein the memory 110 is used to store program codes, and the processor 120 is used to call the program codes to execute the method as described above; please refer to the attached Figure 4 , Figure 4 A schematic diagram of the hardware structure of the electric energy recovery system provided in some embodiments of the present application.

[0118] Among them, the processor 120 is used to provide computing and control capabilities to control the energy recovery system to perform corresponding tasks, for example, to control the energy recovery system to perform the energy recovery method of an electric bicycle in any of the above-mentioned method embodiments, the method comprising: obtaining target obstacle information located in front of the vehicle during the driving of the electric bicycle; determining the danger factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle; obtaining obstacle crossing associated parameters of the electric bicycle, wherein the obstacle crossing associated parameters include tire width, drive motor power and suspension system shock absorption level; correcting the danger factor according to the obstacle crossing associated parameters of the electric bicycle and the target obstacle information to obtain a target danger factor; determining the obstacle avoidance type to be activated according to the target danger factor of the electric bicycle, wherein the obstacle avoidance type includes one of emergency obstacle avoidance and preventive obstacle avoidance; when it is determined that the obstacle avoidance type to be activated by the vehicle is emergency obstacle avoidance, turning on the energy recovery circuit and controlling the drive motor of the electric bicycle to perform a first acceleration brake to perform energy recovery in a first state.

[0119] The processor 120 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip or any combination thereof; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD) or a combination thereof. The above-mentioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL) or any combination thereof.

[0120] The memory 110 is a non-transient computer-readable storage medium that can be used to store non-transient software programs, non-transient computer executable programs and modules, such as program instructions / modules corresponding to the electric energy recovery method for an electric bicycle in the embodiment of the present application. The processor 120 can implement the electric energy recovery method for an electric bicycle in any of the above method embodiments by running the non-transient software programs, instructions and modules stored in the memory 110.

[0121] Specifically, the memory 110 may include a volatile memory (VM), such as a random access memory (RAM); the memory 110 may also include a non-volatile memory (NVM), such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD) or other non-transitory solid-state storage device; the memory 110 may also include a combination of the above types of memory.

[0122] In summary, the electric energy recovery system of the present application adopts the technical solution of any one of the above-mentioned electric energy recovery method embodiments of the electric bicycle, and therefore, has at least the beneficial effects brought by the technical solution of the above-mentioned embodiments, which will not be described one by one here.

[0123] The embodiment of the present application also provides a computer-readable storage medium, such as a memory including a program code, and the program code can be executed by a processor to complete the electric energy recovery method of the electric bicycle in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), a magnetic tape, a floppy disk, and an optical data storage device.

[0124] The embodiment of the present application also provides a computer program product, which includes one or more program codes, and the program codes are stored in a computer-readable storage medium. The processor of the electric energy recovery system reads the program code from the computer-readable storage medium, and the processor executes the program code to complete the steps of the electric energy recovery method for the electric bicycle provided in the above embodiment.

[0125] A person skilled in the art will appreciate that all or part of the steps for implementing the above embodiments may be accomplished by hardware or by hardware associated with a program code, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0126] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] Through the description of the above implementation methods, ordinary technicians in this field can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Ordinary technicians in this field can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0128] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. An electric energy recovery method for an electric bicycle, applied to an electric energy recovery system, wherein the electric energy recovery system comprises an obstacle detection device and an electric energy recovery device, wherein the electric energy recovery device comprises a driving motor for driving the electric bicycle, an electric energy recovery control circuit and an energy storage battery, wherein: The method comprises: Obtain target obstacle information located in front of the vehicle during the driving of the electric bicycle; Determine the danger factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle; Obtaining obstacle-crossing related parameters of the electric bicycle, wherein the obstacle-crossing related parameters include tire width, drive motor power, and suspension system shock absorption level; Correcting the risk factor according to the obstacle-crossing associated parameters of the electric bicycle and the target obstacle information to obtain a target risk factor; Determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle, wherein the obstacle avoidance type includes one of emergency obstacle avoidance and preventive obstacle avoidance, wherein the emergency obstacle avoidance indicates that the vehicle needs emergency braking, and the preventive obstacle avoidance indicates that the vehicle does not need emergency braking, but only needs slow braking to prevent potential risks in advance; When it is determined that the obstacle avoidance type to be initiated by the vehicle is emergency obstacle avoidance, the energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to perform braking at a first acceleration to perform electric energy recovery in a first state.

2. The electric energy recovery method for an electric bicycle according to claim 1, characterized in that: After determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle, the method further includes: When it is determined that the obstacle avoidance type that the vehicle needs to initiate is preventive obstacle avoidance, the energy recovery circuit is turned on and the drive motor of the electric bicycle is controlled to perform braking at a second acceleration to perform electric energy recovery in a second state, wherein the second acceleration is less than the first acceleration.

3. The electric energy recovery method for an electric bicycle as claimed in claim 2, characterized in that: The method of turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to perform a first acceleration brake to recover electric energy in a first state includes: Turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to brake and decelerate with a first braking current to recover electric energy in a first state; and / or, The method of turning on the energy recovery circuit and controlling the driving motor of the electric bicycle to perform braking at a second acceleration to recover electric energy in a second state includes: The energy recovery circuit is turned on and the driving motor of the electric bicycle is controlled to brake and decelerate with a second braking current to perform electric energy recovery in a second state, wherein the first braking current is greater than the first braking current.

4. The electric energy recovery method for an electric bicycle as claimed in claim 1, characterized in that: The obstacle detection device includes a camera and an infrared sensor, the target obstacle information includes the distance information between the electric bicycle and the target obstacle and the size information of the target obstacle, and the step of obtaining the target obstacle information located in front of the electric bicycle during its travel includes: Acquiring size information of a target obstacle located in front of the electric bicycle during its travel based on the target obstacle image captured by the camera; and The distance information between the electric bicycle and the target obstacle is obtained based on the infrared sensor.

5. The electric energy recovery method for an electric bicycle as claimed in claim 4, characterized in that: The size information of the target obstacle includes the length size information of the target obstacle, and determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes: Obtain a relationship mapping table between obstacle length, vehicle speed and vehicle risk factor; The relationship mapping table is queried according to the length of the target obstacle and the current speed of the vehicle to determine the danger factor of the electric bicycle.

6. The electric energy recovery method for an electric bicycle as claimed in claim 4, characterized in that: The size information of the target obstacle includes height size information of the target obstacle, and determining the risk factor of the electric bicycle according to the target obstacle information and the current speed of the vehicle includes: Obtain a relationship mapping table between obstacle height, vehicle speed and vehicle risk factor; The relationship mapping table is queried according to the height size of the target obstacle and the current speed of the vehicle to determine the danger factor of the electric bicycle.

7. The electric energy recovery method for an electric bicycle as claimed in claim 1, characterized in that: The step of correcting the risk factor according to the obstacle-crossing associated parameter of the electric bicycle and the target obstacle information to obtain a target risk factor includes: Determining a quantitative evaluation value of obstacle crossing performance according to obstacle crossing associated parameters of the electric bicycle; Determining an obstacle force evaluation value of the target obstacle according to the target obstacle information; Correcting the risk factor according to the quantified evaluation value of the obstacle crossing performance of the electric bicycle and the obstacle force evaluation value of the target obstacle to obtain a target risk factor; Among them, when the quantitative evaluation value of the obstacle crossing performance of the electric bicycle is greater than or equal to the obstacle force evaluation value of the target obstacle, the risk factor is reversely corrected to reduce the target risk factor; when the quantitative evaluation value of the obstacle crossing performance of the electric bicycle is less than the obstacle force evaluation value of the target obstacle, the risk factor is positively corrected to increase the target risk factor.

8. The electric energy recovery method for an electric bicycle as claimed in claim 7, characterized in that: The step of determining the obstacle crossing performance quantitative evaluation value according to the obstacle crossing associated parameters of the electric bicycle comprises: The obstacle-crossing associated parameters of the electric bicycle are input into the obstacle-crossing performance quantitative prediction model to obtain the obstacle-crossing performance quantitative evaluation value, wherein the obstacle-crossing performance quantitative prediction model satisfies the following expression: Wherein, W is the front wheel width of the electric bicycle, W0 is the reference front wheel width, Y1 is the reference obstacle performance quantitative evaluation value under the reference front wheel width, P is the driving motor power, P0 is the reference power of the driving motor, Y2 is the reference obstacle performance quantitative evaluation value under the reference power of the driving motor, Y3 is the obstacle performance quantitative evaluation value when the shock absorption level of the suspension system is greater than or equal to 3, Y4 is the obstacle performance quantitative evaluation value when the shock absorption level of the suspension system is less than 3, N is the shock absorption level of the suspension system, and θ1, θ2, and θ3 are the corresponding influence weights respectively.

9. The electric energy recovery method for an electric bicycle as claimed in claim 1, characterized in that: The step of determining the obstacle avoidance type to be activated according to the target risk factor of the electric bicycle includes: If the target risk factor of the electric bicycle is greater than or equal to the risk factor threshold, determining that the obstacle avoidance type to be activated is emergency obstacle avoidance; If the target risk factor of the electric bicycle is less than the risk factor threshold, it is determined that the obstacle avoidance type to be activated is preventive obstacle avoidance.

10. An electric energy recovery system, characterized in that: include: An obstacle detection device, the obstacle detection device comprising a camera and an infrared sensor; An electric energy recovery device, the electric energy recovery device comprising a driving motor for driving an electric bicycle, an electric energy recovery control circuit and an energy storage battery; A memory, the memory being used to store program codes; as well as, A processor, wherein the processor is used to call the program code to execute the method according to any one of claims 1 to 9.

11. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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