Road condition recognition method, deceleration control method, and related devices

Abstract

The application discloses a road condition identification method, a deceleration control method and related equipment thereof. The method comprises the following steps: when the motor state of an electric vehicle meets a deceleration control condition, a preset electric vehicle running resistance acquisition function is called, and the real-time running resistance of the electric vehicle is acquired through the running resistance acquisition function; the real-time running resistance is compared with a road condition identification threshold value, and the road condition in which the electric vehicle is currently running is identified. That is, the current road condition is identified by using the resistance relationship value between the resistance of the electric vehicle running on a flat road and the resistance of the electric vehicle running on a slope, and the real-time running resistance of the electric vehicle, and the road condition is identified as an uphill, a downhill or a flat road.

Description

Technical Field

[0001] This application relates to the field of electric engineering machinery, and in particular to a road condition identification method, a deceleration control method, and related equipment. Background Technology

[0002] Electric vehicles play a crucial role in material handling equipment, serving as highly efficient devices for mechanized loading, unloading, stacking, and short-distance transportation. Looking at the electric vehicle industry as a whole, electrification, intelligentization, and industry consolidation are the three major development trends. Therefore, electric forklifts are increasingly favored by customers. Compared to traditional gasoline-powered forklifts, electric forklifts use an electric motor and electronic control system instead of a transmission engine, with the motor directly driving the wheels via a reducer.

[0003] Based on electric vehicle applications, current electric forklift manufacturers require all drives to operate in speed mode. However, in speed mode, the motor speed is provided by the throttle opening, and the motor still outputs torque even after the throttle is released. Traditional engines, on the other hand, output no torque after the throttle is released, resulting in different performance characteristics between electric and traditional forklifts under different road conditions. For example, a traditional forklift decelerates faster and farther uphill than on flat ground, while an electric forklift exhibits essentially the same deceleration performance across various road conditions.

[0004] In practical use, customers require electric forklifts to perform similarly to traditional gasoline forklifts, decelerating as smoothly as possible on flat roads and with the shortest possible deceleration distance on uphill roads. However, current electric forklift motors operate at a fixed speed, resulting in roughly the same deceleration time and distance regardless of road conditions. This lack of deceleration control flexibility fails to meet current customer needs and degrades the driving experience. Therefore, the issue of identifying road conditions for electric forklifts to match their speed with actual road conditions urgently needs to be addressed. Summary of the Invention

[0005] In view of this, embodiments of this application provide a road condition identification method, a deceleration control method, and related equipment, aiming to solve the technical problem that existing electric forklifts are difficult to identify road conditions and cannot meet customers' deceleration needs for different road conditions.

[0006] This application provides a road condition identification method, the method comprising:

[0007] When the motor status of the electric vehicle meets the deceleration control conditions, the preset electric vehicle driving resistance acquisition function is called to obtain the real-time driving resistance of the electric vehicle.

[0008] The real-time driving resistance is compared with a preset road condition identification threshold to identify the current road condition of the electric vehicle.

[0009] In one possible implementation of this application, the road condition identification threshold is determined based on the flat road driving resistance of the electric vehicle and the resistance relationship between slope driving and flat road driving. The flat road driving resistance includes the initial flat road driving resistance and the first successfully acquired flat road driving resistance.

[0010] Before the step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle, the following steps are included:

[0011] When the driving resistance is acquired, determine whether the real-time driving resistance is acquired for the first time.

[0012] If the real-time driving resistance is obtained for the first time, then the flat road driving resistance is the initialized flat road driving resistance.

[0013] The step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle includes:

[0014] The real-time driving resistance is compared with the road condition identification threshold corresponding to the initialized flat road driving resistance to identify the current road condition of the electric vehicle. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0015] In one possible implementation of this application, after the step of determining whether the real-time driving resistance is obtained for the first time, the method includes:

[0016] If the real-time driving resistance is not obtained for the first time, then the flat road driving resistance is the flat road driving resistance obtained for the first time.

[0017] The step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle includes:

[0018] The real-time driving resistance is compared with the road condition identification threshold corresponding to the first successfully obtained flat road driving resistance to identify the current road condition of the electric vehicle. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0019] In one possible implementation of this application, after the step of identifying the current road conditions of the electric vehicle, the following steps are included:

[0020] If the road condition is identified as a flat road, the current real-time driving resistance is assigned to the flat road driving resistance to obtain the first successfully acquired flat road driving resistance.

[0021] In one possible implementation of this application, the step of calling a preset electric vehicle driving resistance acquisition function and obtaining the real-time driving resistance of the electric vehicle through the driving resistance acquisition function when the motor state of the electric vehicle meets the deceleration control conditions includes:

[0022] When the motor status of the electric vehicle meets the deceleration control conditions, determine whether the vehicle mass refresh flag is in the state of re-acquiring real-time driving resistance.

[0023] When the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance, the time value and total torque of the motor are recorded, and the real-time driving resistance is calculated based on the time value and the total torque.

[0024] If the vehicle weight refresh flag is in the state of reacquiring real-time driving resistance, the vehicle weight refresh flag is initialized so that it is not in the state of reacquiring real-time driving resistance, and the steps of recording the motor time value and total torque continue; the real-time driving resistance is calculated based on the time value and the total torque.

[0025] In one possible implementation of this application, the step of recording the motor time value and total torque when the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance includes:

[0026] When the vehicle quality refresh flag is not in the state of re-acquiring real-time driving resistance, it enters the preparation state for acquiring driving resistance and determines whether to allow the acquisition of driving resistance.

[0027] If the driving resistance is allowed to be obtained and the current speed of the motor meets the state transition conditions, the system will transition to the in-process state and record the motor's time value and total torque.

[0028] In one possible implementation of this application, the step of determining whether to allow the acquisition of driving resistance includes:

[0029] In the preparation state, the conditions for obtaining permission for the motor to enter the deceleration control state are obtained;

[0030] If the current speed of the motor meets the allowed acquisition condition, then the allowed acquisition of driving resistance is determined.

[0031] This application also provides a deceleration control method, which includes the road condition identification method described above, and further includes the following after the step of identifying the road condition currently in which the electric vehicle is traveling:

[0032] Based on the identification results of the current road conditions of the electric vehicle, a corresponding deceleration curve is selected so that the electric vehicle motor drives the electric vehicle to travel under different road conditions according to the deceleration curve. The deceleration curve makes the deceleration of the electric vehicle controlled by the motor consistent with the deceleration of the vehicle controlled by the engine under different road conditions.

[0033] This application also provides a road condition identification device, the device comprising:

[0034] The resistance acquisition module is used to call a preset electric vehicle driving resistance acquisition function when the motor state of the electric vehicle meets the deceleration control conditions, and to obtain the real-time driving resistance of the electric vehicle through the driving resistance acquisition function.

[0035] The road condition identification module is used to compare the real-time driving resistance with a preset road condition identification threshold to identify the current road condition of the electric vehicle.

[0036] This application also provides a road condition identification device, which is a physical node device. The road condition identification device includes: a memory, a processor, and a program of the deceleration control method stored in the memory and executable on the processor. When the program of the deceleration control method is executed by the processor, it can implement the steps of the deceleration control method as described above.

[0037] To achieve the above objectives, a computer-readable storage medium is also provided, on which a deceleration control program is stored, which, when executed by a processor, implements the steps of any of the deceleration control methods described above.

[0038] This application provides a road condition identification method, a deceleration control method, and related equipment. When the motor state of an electric vehicle meets the deceleration control conditions, a preset electric vehicle driving resistance acquisition function is invoked to obtain the real-time driving resistance of the electric vehicle. The real-time driving resistance is compared with a preset road condition identification threshold to identify the current road condition of the electric vehicle. In this application, the current road condition is identified by utilizing the resistance relationship between the electric vehicle's resistance when driving on a flat road and on a slope, as well as the current real-time driving resistance of the electric vehicle. The road condition is identified as uphill, downhill, or flat. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the first embodiment of the road condition identification method of this application;

[0040] Figure 2 This is a schematic diagram of the electric vehicle driving resistance acquisition function in the second embodiment of the road condition identification method of this application;

[0041] Figure 3This is a schematic diagram of the force analysis of an electric vehicle in the third embodiment of the road condition identification method of this application;

[0042] Figure 4 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application;

[0043] Figure 5 This is a schematic diagram of the functional modules of a preferred embodiment of the road condition identification device of this application. Detailed Implementation

[0044] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0045] This application provides a road condition identification method. In one embodiment of this road condition identification method, it is applied to a road condition identification device, with reference to... Figure 1 The method includes:

[0046] Step S10: When the motor state of the electric vehicle meets the deceleration control conditions, a preset electric vehicle driving resistance acquisition function is called to obtain the real-time driving resistance of the electric vehicle through the driving resistance acquisition function.

[0047] Step S20: Compare the real-time driving resistance with the preset road condition identification threshold to identify the current road condition of the electric vehicle.

[0048] This embodiment aims to identify the current road conditions of the electric forklift by outputting torque.

[0049] Specifically, in this application, the current road conditions are identified by using the resistance relationship between the resistance of the electric vehicle when driving on a flat road and driving on a slope, as well as the current real-time driving resistance of the electric vehicle, and the road conditions are identified as uphill, downhill or flat.

[0050] In this embodiment, the specific application scenario is:

[0051] In practical use, customers require existing electric forklifts to perform similarly to traditional gasoline forklifts, decelerating as smoothly as possible on flat roads and with minimal deceleration distance on uphill sections. However, current electric forklift motors operate at a fixed speed, resulting in roughly the same deceleration time and distance regardless of road conditions. This lack of deceleration control flexibility fails to meet current customer needs and degrades the driving experience. Therefore, the issue of identifying road conditions to match the electric forklift's speed to actual road conditions urgently needs to be addressed.

[0052] As an example, the road condition identification method can be applied to a road condition identification system, which is applied to a road condition identification device.

[0053] As an example, the road condition identification method refers to vehicles that use a motor-driven reducer to drive the wheels.

[0054] As an example, vehicles include electric engineering vehicles, such as electric forklifts, electric stackers, and electric tractors. The following explanation uses electric forklifts as an example.

[0055] As an example, the drives of electric forklifts all operate in speed mode, where the motor speed is provided by the throttle opening, and the motor still outputs torque even when the throttle is released.

[0056] As an example, real-time driving resistance and flat road driving resistance are obtained by directly reading the torque at the motor shaft end.

[0057] The specific steps are as follows:

[0058] Step S10: When the motor state of the electric vehicle meets the deceleration control conditions, a preset electric vehicle driving resistance acquisition function is called to obtain the real-time driving resistance of the electric vehicle through the driving resistance acquisition function.

[0059] As an example, the deceleration control of an electric forklift is achieved through the motor-controlled deceleration process after the throttle is released. Therefore, before implementing the road condition recognition method, it is necessary to determine whether the electric forklift meets the deceleration control conditions. Only when the electric forklift's motor state (or drive mode) meets the deceleration control conditions will the deceleration of the electric forklift be controlled according to the current road conditions to provide the driver with a better driving experience.

[0060] As an example, the deceleration control condition can be that the throttle-set speed is lower than a preset speed value, where the throttle-set speed is the target speed of the motor. That is, when the target speed of the motor is less than the preset speed value, it indicates that the motor has entered a deceleration state, and deceleration control of the motor is required.

[0061] As an example, the preset speed value is an empirical value, set according to actual needs. For instance, if the throttle input speed is below 20 rpm, then the deceleration control condition is that the throttle input speed is less than 20 rpm.

[0062] As an example, a deceleration control condition could also be that the driver intends to stop the vehicle.

[0063] As an example, the driver's intention to stop is determined by the target speed set by the Vcu (vehicle control unit, electronic control system). The Vcu target speed is actually the depth of the driver's accelerator pedal. When the driver releases the accelerator, the target speed is 0 rpm. If the target speed remains at 0 rpm for a period of time, it is considered that the driver intends to decelerate and stop.

[0064] As an example, the driving resistance acquisition function refers to a function or algorithm used to obtain the real-time driving resistance of an electric forklift.

[0065] As an example, when the electric forklift's motor status meets the deceleration control conditions, the driving resistance acquisition function is called and executed. The driving resistance acquisition function provides the resistance of the electric forklift under the current road conditions, i.e., the real-time driving resistance.

[0066] As an example, real-time driving resistance includes rolling friction resistance, wind resistance, and other resistances. Since the maximum driving speed of an electric vehicle does not exceed 20 km / h, the wind resistance is very small and can be ignored.

[0067] In this embodiment, when the electric forklift is in deceleration control state, the real-time driving resistance of the electric forklift is obtained through a resistance acquisition function. This is used to identify the current road conditions by utilizing the resistance relationship between the electric vehicle's resistance when driving on flat roads and on slopes, thereby realizing the road condition identification function of the electric forklift.

[0068] Step S20: Compare the real-time driving resistance with the preset road condition identification threshold to identify the current road condition of the electric vehicle.

[0069] As an example, the road condition identification threshold is determined based on the resistance of the electric vehicle when driving on a flat road, and the resistance relationship between driving on a slope and driving on a flat road.

[0070] As an example, the resistance to driving on a flat road refers to the total resistance generated when an electric vehicle is driving on a flat road. The total resistance includes rolling friction, road resistance, and wind resistance. Since the electric vehicle operates at a relatively low speed, the wind resistance is correspondingly very small and can be ignored.

[0071] As an example, the road condition identification threshold refers to the threshold used to identify different road conditions, including flat road conditions, uphill road conditions, and downhill road conditions. Therefore, there are two road condition identification thresholds: a first threshold and a second threshold. Uphill road conditions correspond to the first threshold, and downhill road conditions correspond to the second threshold; thus, the first threshold is greater than the second threshold.

[0072] As an example, electric forklifts experience additional road resistance when traveling on inclines or declines compared to flat roads, where they only experience rolling friction and wind resistance. Therefore, there is a relationship between the total resistance of an electric forklift traveling on an incline and on a flat road. Based on this relationship, and the resistance encountered on a flat road, a road condition identification threshold can be derived.

[0073] As an example, in the road condition identification threshold, the first threshold a1 = k1 * f, where k1 is the relationship between the resistance of the electric vehicle when driving uphill and on a flat road, and f is the resistance when driving on a flat road. The second threshold a2 = -k2 * f, where k2 is the relationship between the resistance of the electric vehicle when driving downhill and on a flat road, and f is the resistance when driving on a flat road.

[0074] As an example, road condition identification thresholds are obtained, including a first threshold a1 and a second threshold a2. If the real-time driving resistance is greater than the first threshold a1, the road surface corresponding to the real-time driving resistance is uphill, and the identification result is uphill road condition; if the real-time driving resistance is less than the second threshold a2, the road surface corresponding to the real-time driving resistance is downhill, and the identification result is downhill road condition; if the real-time driving resistance is greater than the second threshold a2 and less than the first threshold a1, the road surface corresponding to the real-time driving resistance is flat road, and the identification result is flat road condition.

[0075] In this embodiment, the resistance relationship between different resistance values ​​when the electric forklift travels on a slope and on a flat road is used to determine different road condition identification thresholds, improving the accuracy of the road condition identification thresholds. By comparing the real-time driving resistance generated by the electric vehicle on the current road surface with the road condition identification threshold when the motor state of the electric vehicle meets the deceleration control conditions, the current road condition is quickly identified. This allows for subsequent adjustments to different deceleration curves based on different road conditions, meeting the deceleration time and distance requirements for different road conditions, thereby providing the driver with a better driving experience.

[0076] As an example, before the step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle, the following steps are included:

[0077] Step S21: When the driving resistance acquisition is completed, determine whether the real-time driving resistance is acquired for the first time.

[0078] Step S22: If the real-time driving resistance is obtained for the first time, then the flat road driving resistance is the initialized flat road driving resistance.

[0079] As an example, when the driving resistance acquisition completion flag is TRUE, it is determined whether the initial acquisition flag corresponding to the real-time driving resistance is FALSE; if the initial acquisition flag is FALSE, that is, the driving resistance acquisition is complete, then the flat road driving resistance is the initialized flat road driving resistance.

[0080] As an example, the resistance to driving on flat roads includes the initial resistance and the resistance achieved on the first successful driving on flat roads. The initial resistance to driving on flat roads refers to the initial value f0 of the electric vehicle's initial driving resistance, i.e., the ideal value. f0 = μmg, where μ is the ideal rolling friction coefficient, m is the vehicle's mass (kg), and g is the gravitational acceleration (9.8 m / s²). 2 .

[0081] As an example, the initial successful acquisition of the flat road driving resistance f1 is a measured value. The rolling friction coefficient derived from f1 is likely to differ from the ideal rolling friction coefficient. Therefore, the real-time driving resistance initially acquired after the electric forklift is powered on may not reflect the resistance under flat road conditions; the electric vehicle may be traveling uphill or downhill. Therefore, it is necessary to compare f0 to determine whether f1 represents the flat road driving resistance. f1, being a measured value, more closely reflects the actual rolling friction coefficient under real-world road conditions (potentially a cement flat road, a slag flat road, or a loess flat road). Therefore, using the initially successfully acquired real-time driving resistance as the flat road driving resistance helps distinguish different road conditions and improves the accuracy of road condition identification.

[0082] As an example, the driving resistance acquisition completion flag indicates whether the real-time driving resistance of the electric vehicle has been acquired using the driving resistance acquisition function. If completed, the driving resistance acquisition completion flag is TRUE; otherwise, it is FALSE. Only when the driving resistance acquisition completion flag is TRUE (i.e., the process of acquiring the real-time driving resistance of the electric vehicle using the driving resistance acquisition function is complete) is the real-time driving resistance assessed to identify the current road conditions.

[0083] As an example, the first acquisition flag indicates whether the currently acquired real-time driving resistance is the first acquisition. The first acquisition flag is used to determine whether the flat road driving resistance is the initialized flat road driving resistance or the first successfully acquired flat road driving resistance.

[0084] As an example, the initial acquisition flags include FALSE and TRUE. If the initial acquisition flag is FALSE, it indicates the first acquisition, and the initial value of the driving resistance f0 is taken as the driving resistance on a flat road.

[0085] As an example, the step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle includes:

[0086] Step S23: Compare the real-time driving resistance with the road condition identification threshold corresponding to the initialized flat road driving resistance to identify the current road condition of the electric vehicle. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0087] The road condition identification threshold is determined based on the resistance of the electric vehicle on a flat road and the resistance relationship between driving on a slope and driving on a flat road.

[0088] As an example, if the initial flag is FALSE, the initial driving resistance value f0 is taken as the driving resistance on a flat road. In the road condition identification threshold, the first threshold a1' = k1 * f0, and the second threshold a2' = -k2 * f0. Therefore, if the real-time driving resistance is greater than the first threshold a1', the road surface corresponding to the real-time driving resistance is uphill, and the identification result is uphill road condition. If the real-time driving resistance is less than the second threshold a2', the road surface corresponding to the real-time driving resistance is uphill, and the identification result is uphill road condition. If the real-time driving resistance is greater than the second threshold a2' and less than the first threshold a1', the road surface corresponding to the real-time driving resistance is flat, and the identification result is flat road condition.

[0089] As an example, after the step of determining whether the real-time driving resistance is being obtained for the first time, the following steps are included:

[0090] Step S24: If the real-time driving resistance is not obtained for the first time, then the flat road driving resistance is the flat road driving resistance obtained for the first time.

[0091] The step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle includes:

[0092] Step S25: Compare the real-time driving resistance with the road condition identification threshold corresponding to the first successfully obtained flat road driving resistance to identify the current road condition of the electric vehicle. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0093] As an example, if the initial acquisition flag is TRUE, then the flat road driving resistance is the flat road driving resistance of the first successful acquisition. It can be understood that if the initial acquisition flag is TRUE, it is a non-first acquisition, and the real-time driving resistance f1 of the first successful acquisition is used as the flat road driving resistance. Therefore, the road condition identification threshold is determined by the real-time driving resistance f1 of the first successful acquisition. In the road condition identification threshold, the first threshold a1” = k2*f1, and the second threshold a2” = -k2*f1.

[0094] As an example, after the step of identifying the current road conditions of the electric vehicle, the process includes:

[0095] Step S26: If the road condition is identified as a flat road condition, the current real-time driving resistance is assigned to the flat road driving resistance to obtain the first successfully acquired flat road driving resistance.

[0096] As an example, if the road condition is identified as a flat road, the initial acquisition flag is set to TRUE; the current real-time driving resistance is assigned to the flat road driving resistance, resulting in the first successfully acquired flat road driving resistance. This is understandable because when the acquired real-time driving resistance is determined to be flat road driving resistance based on the initial driving resistance value f0, this real-time driving resistance matches the actual road conditions. In other words, using this real-time driving resistance as a criterion for identifying road conditions can improve the accuracy of road condition identification. Therefore, if the road condition corresponding to the current real-time driving resistance is identified as a flat road based on the initial driving resistance value f0, the initial acquisition flag is set to TRUE, thus determining the current real-time driving resistance as the first successfully acquired real-time driving resistance f1.

[0097] As an example, the current real-time driving resistance is assigned to the flat road driving resistance to obtain the flat road driving resistance for the first successful acquisition.

[0098] As an example, if the initial acquisition flag is TRUE, the first successfully acquired real-time driving resistance f1 is taken as the flat road driving resistance. In the road condition identification threshold, the first threshold a1” = k2 * f1, and the second threshold a2” = -k2 * f1. Therefore, if the real-time driving resistance is greater than the first threshold a1”, the road surface corresponding to the acquisition of the real-time driving resistance is uphill, and the identification result is uphill road condition. If the real-time driving resistance is less than the second threshold a2”, the road surface corresponding to the acquisition of the real-time driving resistance is downhill, and the identification result is downhill road condition. If the real-time driving resistance is greater than the second threshold a2” and less than the first threshold a1”, the road surface corresponding to the acquisition of the real-time driving resistance is flat road, and the identification result is flat road condition.

[0099] In this embodiment, the road condition corresponding to the real-time driving resistance is identified by using a road condition identification threshold determined by the driving resistance on flat roads. This allows for rapid acquisition of road condition information, facilitating the selection of different deceleration curves based on varying road conditions to meet the deceleration time and distance requirements. Furthermore, by comparing the driving resistance on flat roads with the initial value, the driving resistance on flat roads that matches the actual road conditions can be determined, thus improving the accuracy of the identification.

[0100] This application provides a road condition identification method, related equipment, and a method for identifying road conditions. Compared to current electric forklifts, which struggle to identify road conditions and meet customer deceleration requirements for different road conditions, this application addresses this by calling a preset electric vehicle driving resistance acquisition function when the electric vehicle's motor status meets deceleration control conditions. The function obtains the real-time driving resistance of the electric vehicle; this real-time driving resistance is then compared with a preset road condition identification threshold to identify the current road condition. Specifically, this application utilizes the resistance relationship between the electric vehicle's resistance on flat roads and on slopes, along with the current real-time driving resistance, to identify the current road condition as uphill, downhill, or flat.

[0101] As an example, electric vehicle road condition recognition includes the following steps:

[0102] Step 1: Begin.

[0103] Step 2: Power on and initialize the electric vehicle. Calculate the initial resistance value f0 for driving on flat roads based on the preset electric vehicle mass, transmission ratio, wheel radius, and rolling friction coefficient. Where f0 = motor shaft torque * wheel transmission ratio * transmission efficiency / wheel radius, thus calculating the motor shaft torque.

[0104] Step 3: Call the electric vehicle driving resistance acquisition function to obtain the real-time driving resistance of the electric vehicle. When the real-time driving resistance is successfully obtained, the driving resistance acquisition completion flag is set to TRUE; otherwise, it is set to FALSE.

[0105] Step 4: When the driving resistance acquisition completion flag is TRUE, determine whether the currently acquired real-time driving resistance is the first acquisition by using the first acquisition flag.

[0106] Step 5: If the initial acquisition flag is FALSE, meaning it's the first acquisition, then compare the real-time driving resistance f1 with the initial driving resistance value f0. Obtain the relationship value k1 between the electric vehicle's resistance when driving uphill and on a flat road, and the relationship value k2 between the electric vehicle's resistance when driving downhill and on a flat road. If the real-time driving resistance f1 > k1*f0, then the current driving condition is uphill; if f1 < -k2*f0, then the current driving condition is downhill; if f1 ≥ -k2*f0 and f1 ≤ k1*f0, then the current driving condition is flat.

[0107] If the current road condition is flat, the initial acquisition flag is set to TRUE. The real-time driving resistance f1 corresponding to the flat road is used as the flat road condition for subsequent road condition identification.

[0108] If the initial acquisition flag is TRUE, meaning it's not the first acquisition, then the real-time driving resistance f2 is used for identification, along with the real-time driving resistance f1 used for flat road driving. The relationship value k1 between the electric vehicle's resistance when driving uphill and on a flat road, and the relationship value k2 between the electric vehicle's resistance when driving downhill and on a flat road, are obtained. If the real-time driving resistance f2 > k1*f1, the current driving condition is uphill; if f2 < -k2*f1, the current driving condition is downhill; if f2 ≥ -k2*f1 and f2 ≤ k1*f1, the current driving condition is flat.

[0109] Step 7: End.

[0110] Based on the first embodiment of the road condition identification method described above, a second embodiment of the road condition identification method is proposed, with reference to... Figure 2 The step of calling a preset electric vehicle driving resistance acquisition function and obtaining the real-time driving resistance of the electric vehicle through the driving resistance acquisition function when the motor state of the electric vehicle meets the deceleration control conditions includes:

[0111] Step A11: When the motor status of the electric vehicle meets the deceleration control conditions, determine whether the vehicle mass refresh flag is in the state of re-acquiring real-time driving resistance.

[0112] Step A12: When the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance, record the time value and total torque of the motor, and calculate the real-time driving resistance based on the time value and the total torque;

[0113] Step A13: If the vehicle weight refresh flag is in the state of reacquiring real-time driving resistance, initialize the vehicle weight refresh flag so that it is not in the state of reacquiring real-time driving resistance, and continue to execute the step of recording the motor time value and total torque; calculate the real-time driving resistance based on the time value and the total torque.

[0114] As an example, the deceleration control condition can be that the throttle-set speed is lower than a preset speed value, where the throttle-set speed is the target speed of the motor. That is, when the target speed of the motor is less than the preset speed value, it indicates that the motor has entered a deceleration state, and deceleration control of the motor is required.

[0115] As an example, the preset speed value is an empirical value, set according to actual needs. For instance, if the throttle input speed is below 20 rpm, then the deceleration control condition is that the throttle input speed is less than 20 rpm.

[0116] As an example, a deceleration control condition could also be that the driver intends to stop the vehicle.

[0117] As an example, the driver's intention to stop is determined by the target speed set by the Vcu (vehicle control unit, electronic control system). The Vcu target speed is actually the depth of the driver's accelerator pedal. When the driver releases the accelerator, the target speed is 0 rpm. If the target speed remains at 0 rpm for a period of time, it is considered that the driver intends to decelerate and stop.

[0118] As an example, when the motor state of the electric vehicle meets the deceleration control conditions, it is determined whether the vehicle mass refresh flag is FALSE, whereby the mass refresh flag is used to indicate whether to reacquire real-time driving resistance; if the vehicle mass refresh flag is FALSE, the vehicle enters the preparation state for acquiring driving resistance, and it is determined whether to allow the acquisition of driving resistance; if the acquisition of driving resistance is allowed and the current speed of the motor meets the state jump condition, the vehicle jumps to the in progress state and records the motor's time value and total torque; based on the time value and the total torque, the real-time driving resistance is calculated.

[0119] As an example, the electric forklift is powered on and initialized before acquiring the real-time driving resistance. This involves setting the initial vehicle mass to m0, the initial driving resistance to f0, the initial slope to s0, and marking the first resistance acquisition as FALSE. The FALSE flag indicates that the currently acquired real-time driving resistance is the first time it has been acquired.

[0120] As an example, the vehicle weight refresh indicator indicates whether to re-acquire flat road resistance. The vehicle weight refresh indicator includes FALSE and TRUE. When the vehicle weight refresh indicator is FALSE, it is not necessary to re-acquire flat road resistance; the initial resistance value f0 is used as the flat road resistance to identify different road conditions. When the vehicle weight refresh indicator is TRUE, it indicates that it is necessary to re-acquire flat road resistance; that is, to acquire flat road resistance adapted to actual road conditions, and to identify different road conditions based on the re-acquired flat road resistance.

[0121] As an example, if the vehicle weight refresh flag is FALSE, then the vehicle enters the preparation state for obtaining driving resistance.

[0122] As an example, when the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance, the steps of recording the motor time value and total torque include:

[0123] Step B11: When the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance, enter the preparation state for acquiring driving resistance and determine whether to allow the acquisition of driving resistance.

[0124] Step B12: If it is allowed to obtain the driving resistance and the current speed of the motor meets the state jump condition, jump to the in progress state and record the motor time value and total torque.

[0125] As an example, if the vehicle weight refresh flag is not FALSE, after setting the initial acquisition flag to FALSE, the vehicle weight refresh flag is then set to FALSE. It can be understood that if the vehicle weight refresh flag is not FALSE, that is, if the vehicle weight refresh flag is TRUE, it indicates that the flat road driving resistance needs to be reacquired. In this case, the initial acquisition flag is set to FALSE, and the flat road driving resistance is reacquired until the first successfully acquired real-time driving resistance f1' is obtained, which is used to identify road conditions based on the second successfully acquired real-time driving resistance f1'.

[0126] As an example, the readiness status for acquiring driving resistance is used to determine whether it is permissible to acquire real-time driving resistance. Whether it is permissible to acquire real-time driving resistance is indicated by a permission flag. When the permission flag is TRUE, it means that it is permissible to acquire real-time driving resistance; when the permission flag is FALSE, it means that it is not permissible to acquire real-time driving resistance.

[0127] As an example, the step of determining whether to allow the acquisition of driving resistance includes:

[0128] Step C11: In the preparation state, obtain the conditions for the motor to enter the deceleration control state.

[0129] Step C12: If the current speed of the motor meets the allowed acquisition condition, then the allowed acquisition driving resistance is determined.

[0130] As an example, the vehicle enters a preparation state for acquiring driving resistance. In the preparation state, the corresponding permitted acquisition conditions are acquired based on the first acquisition flag, which includes FALSE and TRUE. If the current speed of the motor meets the permitted acquisition conditions, the permitted flag is set to TRUE.

[0131] As an example, in the ready state, the timing value Cnt is cleared to zero, the total torque recording value Trq is cleared to zero, the resistance acquisition completion flag is set to FALSE, and the resistance acquisition in progress flag is set to FALSE.

[0132] If the initial acquisition flag is FALSE, the acquisition condition is to determine whether there is a deviation between the current actual speed of the motor and the preset value, and the deviation is within a certain range (e.g., 20 rpm). If the deviation between the actual speed and the preset value is within 20 rpm, the acquisition flag is set to TRUE.

[0133] If the initial acquisition flag is TRUE, the acquisition condition is to determine whether the driver intends to stop the machine. If the driver intends to stop the machine, the acquisition flag is set to TRUE.

[0134] As an example, the timing value is a variable defined in the driving resistance acquisition function, used to record the time in the constant speed zone. The total torque record is also a user-defined variable, used to record the sum of the real-time torque at the motor shaft end in the constant speed zone. The total torque divided by the timing value yields the average torque during this time, which is the real-time driving resistance.

[0135] As an example, a state transition condition refers to the condition for transitioning from the preparation state obtained from the driving resistance to the in-process state obtained from the driving resistance.

[0136] As an example, the state transition condition is: when the actual rotational speed is greater than or equal to the rotational speed threshold and the allow flag is TRUE, then the state transitions to the in progress state.

[0137] As an example, the actual and target motor speeds obtained during the last run of the driving resistance acquisition function are recorded. The operating trend of the electric forklift is determined by comparing the actual and target speeds. For instance, if the previously acquired actual speed is consistently higher than the currently acquired actual speed, it indicates that the electric forklift is decelerating, and real-time driving resistance acquisition is initiated. The real-time driving resistance can be acquired when the current motor speed meets the state transition condition.

[0138] As an example, in the in-process state: the accumulated timing value Cnt++, the accumulated total torque Trq++, and the resistance acquisition in-process flag set to TRUE. If the timing value Cnt++ is greater than or equal to the constant speed zone holding time T0, it jumps to the acquisition success state; if the timing value Cnt++ is greater than the timeout time T1 or the current speed fluctuation exceeds the fluctuation threshold (e.g., 50 rpm), it jumps to the acquisition failure state. If the timing value Cnt++ is less than the constant speed zone holding time T0 and / or the timing value Cnt++i is less than or equal to the timeout time T1 and / or the current speed fluctuation is less than the fluctuation threshold, it continues in the in-process state, accumulating timing and acquiring the motor shaft torque.

[0139] As an example, if the acquisition fails, the accumulated time value Cnt++ is cleared to zero. If the acquisition succeeds, the initial acquisition flag is checked to determine whether it is FALSE or TRUE, and different real-time driving resistance is output according to the initial acquisition flag.

[0140] As an example, if the initial acquisition flag is FALSE, the average output torque (total torque divided by the average torque obtained from the timing value) is assigned to the real-time driving resistance f1', and the real-time driving resistance f1' is output. This is used to compare the real-time driving resistance f1' with the road condition identification threshold when the initial driving resistance value f0 is used as the driving resistance on a flat road, to determine the current driving road condition.

[0141] As an example, if the initial acquisition flag is TRUE, the average output torque (total torque divided by the average torque obtained from timing values) is assigned to the real-time driving resistance f2, and the real-time driving resistance f2 is output. If the initial acquisition flag is TRUE, it indicates that the initial acquisition was successful, and the successfully acquired real-time driving resistance f1' is used as the road condition identification for flat road driving resistance. Therefore, the real-time driving resistance f2 is output, and f2 is compared with the road condition identification threshold when the successfully acquired real-time driving resistance f1' is used as the flat road driving resistance to determine the current driving road condition.

[0142] As an example, after obtaining a failed or successful state, the system enters an ending state. In the ending state, the resistance acquisition in progress flag is set to FALSE, and the resistance acquisition completion flag is set to TRUE. When the resistance acquisition completion flag is TRUE, the step of determining whether the initial acquisition flag corresponding to the real-time driving resistance is FALSE is executed to determine the driving resistance on flat roads and identify road conditions.

[0143] As an example, at the end state, the accelerator pedal speed is obtained. When the accelerator pedal speed is less than the preset value (such as 20L), it indicates that the electric forklift has entered the deceleration state. Then, it is necessary to identify the current road conditions to adjust the deceleration curve. Therefore, it enters the preparation state for obtaining driving resistance.

[0144] In this embodiment, by using a preset electric vehicle driving resistance acquisition function, the road condition information of the electric vehicle can be identified by the torque output from the motor shaft end (real-time driving resistance) when the electric forklift is in the deceleration control phase, thereby improving the efficiency of road condition identification.

[0145] As an example, calling the preset electric vehicle driving resistance acquisition function, the process of acquiring the resistance during the electric vehicle's driving process includes the following steps:

[0146] Step 1: Begin.

[0147] Step 2: Determine if the vehicle quality refresh flag is set to TRUE. If yes, set the flag to FALSE upon initial acquisition and check if the vehicle quality refresh flag is set to FALSE; otherwise, do not process.

[0148] Step 3: Preparation status: Reset the timing value Cnt to zero, reset the total torque recording value Trq to zero, set the resistance acquisition completion flag to FALSE, and set the resistance acquisition in progress flag to FALSE.

[0149] If the initial flag is FALSE, check if the motor's current actual speed deviates from the preset value by 20 rpm. If so, set the flag to TRUE.

[0150] If the initial flag is TRUE, determine if the driver intends to stop the vehicle. If so, set the flag to TRUE.

[0151] When the actual speed is greater than or equal to the speed threshold and the allow flag is TRUE, the process jumps to the in progress state.

[0152] Step 4: In Progress Status: Timing value Cnt++, total torque Trq++, resistance acquisition in progress flag set to TRUE.

[0153] If the timing value Cnt++ is greater than the constant speed zone holding time T0, then jump to the successful acquisition state;

[0154] If the timing value Cnt++ is greater than the timeout time T1 or the current speed fluctuation exceeds 50 rpm, then jump to the acquisition failure state.

[0155] Step 5: Get the failure status: Clear the timer value Cnt++ to zero and jump to get the completion status.

[0156] Acquisition success status: If the first acquisition flag is FALSE, the first acquisition success flag is set to TRUE, and the real-time driving resistance f1' = total torque Trq++ / timing value Cnt++;

[0157] Otherwise (the initial acquisition flag is TRUE), the real-time resistance value f2 = total torque Trq++ / timing value Cnt++, and jump to the acquisition end state.

[0158] Clear the timing value Cnt++ to zero, and clear the total torque Trq++ to zero.

[0159] Step 6: End Status: Set the resistance acquisition complete flag to TRUE, and the resistance acquisition in progress flag to FALSE.

[0160] If the set speed for the throttle is below 20 rpm, the system will switch to the ready state.

[0161] Based on the first or second embodiment of the road condition identification method described above, a third embodiment of the road condition identification method is proposed. The method further includes:

[0162] Step D11: Determine the resistance relationship between the electric vehicle and the road surface when driving on a slope and on a flat road.

[0163] Step D12: Calculate the road condition identification threshold based on the resistance relationship value.

[0164] As an example, refer to Figure 3 A force analysis of electric vehicle operation was conducted: Electric vehicles experience additional road resistance when traveling on inclines or declines compared to flat roads, while on flat roads, they only experience rolling friction and wind resistance. Since the maximum speed of an electric vehicle does not exceed 20 km / h, wind resistance is very small and can be ignored.

[0165] Rolling friction force: f1=μ(m1+m2)g*Cosα

[0166] Road resistance: f2=(m1+m2)g*Sinα

[0167] The road resistance is the component of the electric forklift's total weight in the direction parallel to the road surface. When going uphill, the road resistance is positive; when going downhill, the road resistance is negative.

[0168] Total resistance uphill: f 总 =f1+f2=(m1+m2)g*(μCosα+Sinα)

[0169] Total downhill resistance: f 总 =f1-f2=(m1+m2)g*(μCosα-Sinα)

[0170] Where α is the road surface slope, and μ is the rolling friction coefficient. The magnitude of μ is mainly related to the material properties and surface conditions (roughness, humidity, etc.) of the objects in contact. Assuming the electric forklift is traveling on a cement road, then μ = 0.02.

[0171] As an example, roads with a slope of less than 5% (i.e., 2.9°) are designated as flat roads, while roads with a slope of more than 5% (i.e., 2.9°) are designated as sloping roads, which are further divided into uphill roads and downhill roads.

[0172] As an example, when the road slope α is 2.9°, according to the above formula for calculating the total resistance on an uphill slope, the total resistance on an uphill slope is approximately 3.5 times the total resistance on a flat road. According to the above formula for calculating the total resistance on a downhill slope, the total resistance on a downhill slope is approximately -1.5 times the total resistance on a flat road. Therefore, the resistance relationship between the electric forklift and its travel on a slope and on a flat road is determined to be 3.5 times for uphill travel and -1.5 times for downhill travel.

[0173] As an example, to obtain the resistance of an electric forklift traveling on a flat road, the road condition identification threshold is calculated based on the relationship between the resistance values ​​when the electric forklift is traveling on an incline and on a flat road. The road condition identification threshold includes a first threshold for identifying uphill road conditions and a second threshold for identifying downhill road conditions.

[0174] As an example, the first threshold is 3.5f and the second threshold is -1.5f, where f is the resistance to driving on flat roads.

[0175] As an example, when an electric forklift is powered on and initialized, the flat road driving resistance refers to the initial value of the driving resistance of the electric vehicle when it is driving on a flat road. This initial value of driving resistance is an ideal value, f0 = μmg.

[0176] As an example, if the first real-time driving resistance obtained after power-on is the resistance on a flat road (the road condition corresponding to the real-time driving resistance is identified as a flat road based on the initial resistance value), then the current real-time driving resistance is more consistent with the actual road conditions. That is, if the first acquisition is successful after power-on, the current real-time driving resistance is used as the driving resistance on a flat road to identify the road conditions.

[0177] In this embodiment, the road conditions currently encountered by the electric forklift are identified by the resistance values ​​when it travels on flat roads, uphill roads, and downhill roads, thus improving the efficiency of road condition identification. Furthermore, when identifying the current road conditions, the initial resistance value is used as the resistance for flat road travel to determine whether the real-time travel resistance obtained after the electric vehicle's power-on initialization reflects the actual road conditions. When this real-time travel resistance reflects the actual road conditions, it is used as the new resistance for flat road travel. This new resistance is then used to identify the road conditions corresponding to subsequently acquired real-time travel resistances. By combining the flat road resistance experienced by the electric vehicle on actual roads or under actual road conditions, the accuracy of road condition identification is improved.

[0178] Based on the first, second, or third embodiment of the road condition identification method described above, a fourth embodiment of the road condition identification method is proposed. This embodiment proposes a deceleration control method. The deceleration control method further includes, after the step of identifying the current road condition of the electric vehicle, a deceleration control method.

[0179] Step S30: Select the corresponding deceleration curve according to the identification result, so that the motor of the electric vehicle drives the electric vehicle to travel under different road conditions according to the deceleration curve, wherein the deceleration curve makes the deceleration of the electric vehicle controlled by the motor under different road conditions consistent with the deceleration of the electric vehicle controlled by the engine.

[0180] This embodiment aims to: identify the current road conditions of the electric forklift by outputting torque, and adjust different deceleration curves accordingly to improve the flexibility of deceleration control of the electric vehicle, so that the electric forklift can perform the same as the traditional oil truck when decelerating, and meet the customer's deceleration needs for different road conditions.

[0181] Specifically, in this application, when the electric vehicle is under deceleration control, the motor is decelerated to match the vehicle's driving state with different road conditions, meeting the deceleration time and distance requirements for different road conditions. This solves the problem that existing electric forklifts exhibit essentially the same deceleration performance under different road conditions (current electric forklifts have fixed motor speeds, resulting in similar deceleration time and distance under different road conditions, leading to poor deceleration control flexibility, failing to meet current customer needs, and reducing the driving experience). In this application, the current road condition is identified using the resistance relationship between the electric vehicle's resistance on flat roads and on slopes, as well as the electric vehicle's current real-time driving resistance, determining whether the road is uphill, downhill, or flat. Different deceleration curves are then selected based on different road conditions to meet the deceleration time and distance requirements for different road conditions, improving the flexibility of the electric forklift's deceleration control. This achieves the same performance as traditional gasoline forklifts, meaning the electric forklift decelerates as smoothly as possible on flat roads and decelerates as little time and distance as possible on uphill roads, meeting current customer needs and providing drivers with a superior driving experience.

[0182] In this embodiment, the specific application scenario is:

[0183] In practical use, customers require existing electric forklifts to perform similarly to traditional gasoline forklifts, decelerating as smoothly as possible on flat roads and with the shortest possible deceleration distance on uphill roads. However, the motors of current electric forklifts operate at a fixed speed, resulting in roughly the same deceleration time and distance regardless of road conditions. This lack of deceleration control flexibility fails to meet current customer needs and degrades the driving experience.

[0184] As an example, the deceleration control method can be applied to a deceleration control system, which is applied to a deceleration control device.

[0185] As an example, the deceleration control method applies to vehicles that use a motor-driven direct-drive reducer to drive the wheels.

[0186] As an example, vehicles include electric engineering vehicles, such as electric forklifts, electric stackers, and electric tractors. The following explanation uses electric forklifts as an example.

[0187] As an example, the drives of electric forklifts all operate in speed mode, where the motor speed is provided by the throttle opening, and the motor still outputs torque even when the throttle is released.

[0188] As an example, the deceleration curve is set according to road conditions (flat road conditions, uphill road conditions, downhill road conditions) and actual deceleration requirements. This deceleration curve is matched to the corresponding road conditions to ensure smooth operation of the electric forklift. For instance, if a customer requires the electric forklift to perform the same as a traditional gasoline forklift, with the smoothest possible deceleration on flat roads and the shortest possible deceleration distance on uphill roads, then the rate of change of the deceleration curve for uphill road conditions will be greater than the rate of change of the deceleration curve for flat road conditions.

[0189] As an example, values ​​are assigned to the corresponding variables based on the identification results, such as 0, 1, and 2. Different values ​​correspond to different deceleration curves, and the appropriate deceleration curve is selected based on the assigned value. For example, "0" corresponds to a deceleration curve for flat roads, "1" corresponds to a deceleration curve for uphill roads, and "2" corresponds to a deceleration curve for downhill roads.

[0190] As an example, the process of selecting the corresponding deceleration curve based on the identification results can also be achieved by establishing a correspondence between different road condition symbols and different deceleration curves, thereby selecting the deceleration curve. Other selection methods are also possible, and no specific limitations are made here.

[0191] In this embodiment, different deceleration curves are selected based on different road conditions to adjust the deceleration during the electric forklift's deceleration process. This allows the electric forklift to perform similarly to a traditional gasoline forklift, decelerating as smoothly as possible on flat roads and minimizing the deceleration distance on uphill roads. In other words, by identifying the current road conditions of the electric vehicle and adjusting the deceleration curve accordingly, the required deceleration time and distance are met for different road conditions, providing the driver with a better driving experience. Furthermore, the identified road condition information can be used in scenarios such as anti-rollover and hill starts, providing a safer and more reliable driving experience.

[0192] This application provides a road condition identification method, a road condition identification method, and related equipment. Compared with the current electric forklifts, which have poor deceleration control flexibility and cannot meet customers' deceleration needs for different road conditions, in this application, when the electric vehicle's motor state meets the deceleration control conditions, a preset electric vehicle driving resistance acquisition function is called to obtain the real-time driving resistance of the electric vehicle. The real-time driving resistance is compared with a preset road condition identification threshold to identify the current road condition of the electric vehicle. Based on the identification result, a corresponding deceleration curve is selected so that the electric vehicle's motor drives the electric vehicle to travel under different road conditions according to the deceleration curve. The deceleration curve ensures that the deceleration of the electric vehicle controlled by the motor under different road conditions is consistent with the deceleration of the vehicle controlled by the engine. In this application, when the electric vehicle is under deceleration control, the motor is decelerated to match the vehicle's driving state with different road conditions, meeting the deceleration time and distance requirements for different road conditions. This solves the problem that existing electric forklifts exhibit essentially the same deceleration performance under different road conditions (current electric forklifts have fixed motor speeds, resulting in similar deceleration time and distance under different road conditions, leading to poor deceleration control flexibility, failing to meet current customer needs, and reducing the driving experience). Specifically, by utilizing the resistance relationship between the electric vehicle's resistance on flat roads and on slopes, as well as the electric vehicle's current real-time driving resistance, the current road condition is identified as uphill, downhill, or flat. Different deceleration curves are then selected based on different road conditions to meet the deceleration time and distance requirements for different road conditions, improving the flexibility of the electric forklift's deceleration control. This achieves the same performance as traditional gasoline forklifts, meaning the electric forklift decelerates as smoothly as possible on flat roads and decelerates as little time and distance as possible on uphill roads, meeting current customer needs and providing the driver with a superior driving experience.

[0193] As an example, based on electric vehicle road condition recognition, different deceleration curves are adjusted to control speed after acquiring road condition information to meet customer requirements for deceleration time and distance. This includes the following steps:

[0194] Step 1: Begin.

[0195] Step 2: Power on and initialize the electric vehicle. Calculate the initial resistance value f0 for driving on flat roads based on the preset electric vehicle mass, transmission ratio, wheel radius, and rolling friction coefficient. Where f0 = motor shaft torque * wheel transmission ratio * transmission efficiency / wheel radius, thus calculating the motor shaft torque.

[0196] Step 3: Call the electric vehicle driving resistance acquisition function to obtain the real-time driving resistance of the electric vehicle. When the real-time driving resistance is successfully obtained, the driving resistance acquisition completion flag is set to TRUE; otherwise, it is set to FALSE.

[0197] Step 4: When the driving resistance acquisition completion flag is TRUE, determine whether the currently acquired real-time driving resistance is the first acquisition by using the first acquisition flag.

[0198] Step 5: If the initial acquisition flag is FALSE, meaning it's the first acquisition, then compare the real-time driving resistance f1 with the initial driving resistance value f0. Obtain the relationship value k1 between the electric vehicle's resistance when driving uphill and on a flat road, and the relationship value k2 between the electric vehicle's resistance when driving downhill and on a flat road. If the real-time driving resistance f1 > k1*f0, then the current driving condition is uphill; if f1 < -k2*f0, then the current driving condition is downhill; if f1 ≥ -k2*f0 and f1 ≤ k1*f0, then the current driving condition is flat.

[0199] If the current road condition is flat, the initial acquisition flag is set to TRUE. The real-time driving resistance f1 corresponding to the flat road is used as the flat road condition for subsequent road condition identification.

[0200] If the initial acquisition flag is TRUE, meaning it's not the first acquisition, then the real-time driving resistance f2 is used for identification, along with the real-time driving resistance f1 used for flat road driving. The relationship value k1 between the electric vehicle's resistance when driving uphill and on a flat road, and the relationship value k2 between the electric vehicle's resistance when driving downhill and on a flat road, are obtained. If the real-time driving resistance f2 > k1*f1, the current driving condition is uphill; if f2 < -k2*f1, the current driving condition is downhill; if f2 ≥ -k2*f1 and f2 ≤ k1*f1, the current driving condition is flat.

[0201] Step 6: Select the corresponding deceleration strategy (deceleration curve) based on the road condition identification results. Assign values ​​based on the road condition identification results: assign "0" to flat roads, "1" to uphill roads, and "2" to downhill roads. Select the speed curve based on the assignment results. "0" corresponds to the deceleration curve for flat roads, "1" to the deceleration curve for uphill roads, and "2" to the deceleration curve for downhill roads.

[0202] Step 7: End.

[0203] Reference Figure 4 , Figure 4 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.

[0204] like Figure 4 As shown, the road condition identification device may include: a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1005.

[0205] Optionally, the road condition recognition device may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optional user interfaces may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).

[0206] Those skilled in the art will understand that Figure 4 The road condition identification device structure shown does not constitute a limitation on the road condition identification device. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0207] like Figure 4 As shown, the memory 1005, serving as a storage medium, may include an operating system, a network communication module, and a deceleration control program. The operating system is a program that manages and controls the hardware and software resources of the road condition identification device, supporting the operation of the deceleration control program and other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1005, as well as communication with other hardware and software in the road condition identification system.

[0208] exist Figure 4 In the road condition identification device shown, the processor 1001 is used to execute the deceleration control program stored in the memory 1005 to implement the steps of the road condition identification method described above.

[0209] The specific implementation method of the road condition identification device in this application is basically the same as the various embodiments of the road condition identification method described above, and will not be repeated here.

[0210] This application also provides a road condition identification device, referring to... Figure 5 The device includes:

[0211] The resistance acquisition module 10 is used to call a preset electric vehicle driving resistance acquisition function when the motor state of the electric vehicle meets the deceleration control conditions, and to acquire the real-time driving resistance of the electric vehicle through the driving resistance acquisition function.

[0212] The road condition identification module 20 is used to compare the real-time driving resistance with a preset road condition identification threshold to identify the current road condition of the electric vehicle.

[0213] In one possible embodiment of this application, the apparatus further includes:

[0214] The judgment module is used to determine whether the real-time driving resistance is being acquired for the first time when the driving resistance acquisition is completed.

[0215] The first determining module is configured to determine the flat road driving resistance as the initialized flat road driving resistance if the real-time driving resistance is the first time it is acquired.

[0216] In one possible implementation of this application, the road condition identification module further includes:

[0217] The first road condition identification submodule is used to compare the real-time driving resistance with the road condition identification threshold corresponding to the initialized flat road driving resistance, and identify the road condition of the electric vehicle currently driving. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0218] The road condition identification threshold is determined based on the resistance of the electric vehicle on a flat road and the resistance relationship between driving on a slope and driving on a flat road.

[0219] In one possible embodiment of this application, the apparatus further includes:

[0220] The second determining module is used to determine the flat road driving resistance as the flat road driving resistance obtained for the first time if the real-time driving resistance is not obtained for the first time.

[0221] In one possible implementation of this application, the road condition identification module further includes:

[0222] The second road condition identification submodule is used to compare the real-time driving resistance with the road condition identification threshold corresponding to the first successfully obtained flat road driving resistance, and identify the road condition of the electric vehicle currently driving. The road condition includes flat road condition, uphill road condition, and downhill road condition.

[0223] In one possible implementation of this application, the road condition identification module further includes:

[0224] The assignment submodule is used to assign the current real-time driving resistance to the flat road driving resistance when the road condition is identified as a flat road condition, so as to obtain the first successfully acquired flat road driving resistance.

[0225] In one possible embodiment of this application, the resistance acquisition module further includes:

[0226] The judgment submodule is used to determine whether the vehicle mass refresh flag is in the state of reacquiring real-time driving resistance when the motor state of the electric vehicle meets the deceleration control conditions.

[0227] The calculation submodule is used to record the time value and total torque of the motor when the vehicle weight refresh flag is not in the state of reacquiring real-time driving resistance, and to calculate the real-time driving resistance based on the time value and the total torque.

[0228] The initialization submodule is used to initialize the vehicle weight refresh flag when the vehicle weight refresh flag is in the state of reacquiring real-time driving resistance, so that the vehicle weight refresh flag is not in the state of reacquiring real-time driving resistance, and to continue to execute the steps of recording the motor time value and total torque; and calculating the real-time driving resistance based on the time value and the total torque.

[0229] The deceleration control conditions include at least one of the following: the throttle speed is lower than the preset speed value; or the driver intends to stop the engine.

[0230] In one possible implementation of this application, the computing submodule further includes:

[0231] The preparation unit is used to enter the preparation state for acquiring driving resistance when the vehicle quality refresh flag is not in the state of reacquiring real-time driving resistance, and to determine whether it is allowed to acquire driving resistance.

[0232] The data recording unit is used to jump to the in-process state and record the motor's time value and total torque if it is allowed to obtain the driving resistance and the current speed of the motor meets the state jump condition.

[0233] In one possible implementation of this application, the acquisition preparation unit further includes:

[0234] The condition acquisition subunit is used to acquire the conditions that allow the motor to enter the deceleration control state during the preparation state.

[0235] A determination subunit is used to determine the allowable driving resistance if the current speed of the motor meets the allowable acquisition condition.

[0236] In one possible embodiment of this application, the apparatus further includes:

[0237] The deceleration control module 30 is used to select a corresponding deceleration curve based on the identification result, so that the motor of the electric vehicle drives the electric vehicle to travel under different road conditions according to the deceleration curve. The deceleration curve makes the deceleration of the electric vehicle controlled by the motor under different road conditions consistent with the deceleration of the vehicle controlled by the engine.

[0238] The specific implementation of the road condition identification device in this application is basically the same as the embodiments of the road condition identification method described above, and will not be repeated here.

[0239] This application provides a computer-readable storage medium that stores one or more programs, which can be executed by one or more processors to implement the steps of the road condition identification method described above.

[0240] The specific implementation of the storage medium in this application is basically the same as the embodiments of the road condition identification method described above, and will not be repeated here.

[0241] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the road condition identification method described above.

[0242] The specific implementation of the computer program product of this application is basically the same as the various embodiments of the road condition identification method described above, and will not be repeated here.

[0243] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0244] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0245] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of a software plus hardware platform, or by hardware, but in many cases the former is a better implementation. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0246] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A road condition identification method, characterized in that, The method includes: When the motor status of the electric vehicle meets the deceleration control conditions, the preset electric vehicle driving resistance acquisition function is called to obtain the real-time driving resistance of the electric vehicle. The real-time driving resistance is compared with the preset road condition identification threshold to identify the current road condition of the electric vehicle. The road condition identification threshold is determined based on the flat road driving resistance of the electric vehicle when driving on a flat road, and the resistance relationship between driving on a slope and driving on a flat road. The flat road driving resistance includes the initial flat road driving resistance and the first successfully obtained flat road driving resistance. The road conditions include flat road conditions, uphill road conditions, and downhill road conditions. If the road condition is identified as a flat road condition, the current real-time driving resistance is assigned to the flat road driving resistance to obtain the first successfully acquired flat road driving resistance. Before the step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle, the following steps are included: When the driving resistance is acquired, determine whether the real-time driving resistance is acquired for the first time. If the real-time driving resistance is obtained for the first time, then the flat road driving resistance is the initialized flat road driving resistance. If the real-time driving resistance is not obtained for the first time, then the flat road driving resistance is the flat road driving resistance obtained for the first time. The step of comparing the real-time driving resistance with the road condition identification threshold to identify the current road condition of the electric vehicle includes: The real-time driving resistance is compared with the road condition identification threshold corresponding to the initialized flat road driving resistance to identify the current road condition of the electric vehicle. Alternatively, the real-time driving resistance is compared with the road condition identification threshold corresponding to the first successfully obtained flat road driving resistance to identify the current road condition of the electric vehicle.

2. The road condition identification method as described in claim 1, characterized in that, The step of calling a preset electric vehicle driving resistance acquisition function and obtaining the real-time driving resistance of the electric vehicle through the driving resistance acquisition function when the motor state of the electric vehicle meets the deceleration control conditions includes: When the motor status of the electric vehicle meets the deceleration control conditions, determine whether the vehicle mass refresh flag is in the state of re-acquiring real-time driving resistance. When the vehicle weight refresh flag is not in the state of re-acquiring real-time driving resistance, the time value and total torque of the motor are recorded, and the real-time driving resistance is calculated based on the time value and the total torque. When the vehicle weight refresh flag is in the state of reacquiring real-time driving resistance, the vehicle weight refresh flag is initialized so that it is not in the state of reacquiring real-time driving resistance, and the steps of recording the motor time value and total torque continue; and the real-time driving resistance is calculated based on the time value and the total torque.

3. The road condition identification method as described in claim 2, characterized in that, When the vehicle weight refresh indicator is not in the state of re-acquiring real-time driving resistance, the steps of recording the motor time value and total torque include: When the vehicle quality refresh flag is not in the state of re-acquiring real-time driving resistance, it enters the preparation state for acquiring driving resistance and determines whether to allow the acquisition of driving resistance. If the driving resistance is allowed to be obtained and the current speed of the motor meets the state transition conditions, the system will transition to the in-process state and record the motor's time value and total torque.

4. The road condition identification method as described in claim 3, characterized in that, The step of determining whether to allow the acquisition of driving resistance includes: In the preparation state, the conditions for obtaining permission for the motor to enter the deceleration control state are obtained; If the current speed of the motor meets the allowed acquisition condition, then the allowed acquisition of driving resistance is determined.

5. A deceleration control method, characterized in that, The road condition identification method as described in any one of claims 1-4 further includes, after the step of identifying the road condition currently in which the electric vehicle is traveling: Based on the identification results of the current road conditions of the electric vehicle, a corresponding deceleration curve is selected so that the electric vehicle motor drives the electric vehicle to travel under different road conditions according to the deceleration curve. The deceleration curve makes the deceleration of the electric vehicle controlled by the motor consistent with the deceleration of the vehicle controlled by the engine under different road conditions.

6. A driver, characterized in that, It includes a memory, a processor, and a deceleration control program stored in the memory and executable on the processor, wherein the processor, when executing the deceleration control program, implements the deceleration control method of claim 5.

7. An electric forklift, characterized in that, Includes the drive unit and electric vehicle body as described in claim 6.

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