An electric work vehicle and a method for detecting heavy load conditions.

Abstract

This disclosure relates to the field of circuits, providing an electric work vehicle and a method for detecting a heavy-load state. The electric work vehicle includes: a motor; a data acquisition module for acquiring at least one mechanical parameter and at least one electrical parameter of the motor, the mechanical parameter including speed parameter, sector time parameter, or torque parameter, and the electrical parameter including bus current parameter, phase current parameter, bus voltage parameter, power parameter, freewheeling time parameter, or duty cycle parameter; a detection module for processing the mechanical and electrical parameters of the motor according to a target calculation formula and generating a target value, the target calculation formula including at least a ratio, the slope of the ratio, or the difference of the ratio; and a judgment module for determining whether the motor is in a heavy-load state based on the target value and a target preset threshold, the target preset threshold being correlated with the target calculation formula. This method can improve the accuracy of determining the heavy-load state.

Description

Technical Field

[0001] This disclosure relates to the field of circuits, and in particular to an electric work vehicle and a method for detecting heavy-load conditions. Background Technology

[0002] Electric work vehicles can include lawnmowers or garden trimmers, etc. Traditional lawnmowers are mainly backpack mowers, handheld mowers, and push mowers, which have low automation, low work efficiency, high labor intensity, and are more harmful to human health. For work areas that require year-round maintenance of large areas of lawn (such as golf courses, football fields, garden lawns, municipal parks, tourist attractions, farms and orchards, and overgrown fields), ride-on lawnmowers have long battery life, flexible operation, and high work efficiency, which can adapt well to this working condition and avoid fatigue and even injury caused by long hours of work.

[0003] Based on energy source, there are currently two main types of ride-on lawnmowers: gasoline engine type and lithium battery rechargeable type. Compared to gasoline engines, lithium battery rechargeable ride-on lawnmowers have significant advantages: all-weather zero emissions, zero fuel consumption, low noise, and simple maintenance (no gasoline, no engine oil, no air filter, no spark plugs, no fuel storage, etc.). In addition, gasoline engines are similar to traditional fuel vehicles, with a complex overall mechanical structure and a differential gear for drive wheel control; while lithium battery rechargeable ride-on lawnmowers use electric motors instead of a fuel engine for drive wheels, allowing for independent control of two (or four) drive wheel motors to achieve straight-line, reverse, turning, and zero-steering motion control, reducing the overall structural complexity of the vehicle and making the control more flexible.

[0004] Currently, the determination of whether an electric work vehicle is in heavy-load mode is usually made using a single parameter, which is not accurate enough and is prone to misjudgment. Summary of the Invention

[0005] This disclosure provides an electric work vehicle and a method for detecting heavy-load conditions, which can at least improve the accuracy of the judgment module in determining the heavy-load mode.

[0006] According to some embodiments of this disclosure, one aspect of this disclosure provides an electric work vehicle, including: a motor; a data acquisition module, the data acquisition module being used to acquire at least one mechanical parameter and at least one electrical parameter of the motor, the mechanical parameter including a speed parameter, a sector time parameter, or a torque parameter, the electrical parameter including a bus current parameter, a phase current parameter, a bus voltage parameter, a power parameter, a freewheeling time parameter, or a duty cycle parameter; a detection module, the detection module being used to process the mechanical parameter and electrical parameter of the motor according to a target calculation formula, and generate a target value, the target calculation formula including at least a ratio, a slope of the ratio, or a difference of the ratio; and a judgment module, the judgment module being used to determine whether the motor is in a heavy load state according to the target value and a target preset threshold, if the target value does not meet the target preset threshold, determining that the motor is in a heavy load state, wherein the target preset threshold is related to the target calculation formula.

[0007] In some embodiments, the speed parameter includes: speed, speed difference, or slope of the speed curve; the sector time parameter includes: sector time, sector time difference, or slope of the sector time curve; the torque parameter includes: torque, torque difference, or slope of the torque curve; the bus current parameter includes: bus current, bus current difference, or slope of the bus current curve; the phase current parameter includes: phase current, phase current difference, or slope of the phase current curve; the bus voltage parameter includes: bus voltage, bus voltage difference, or slope of the bus voltage curve; the power parameter includes: power, power difference, or power slope; the freewheeling time parameter includes: freewheeling time, freewheeling time difference, or slope of the freewheeling time curve; the duty cycle parameter includes: duty cycle parameter, duty cycle parameter difference, or slope of the duty cycle parameter curve; and the target value is the ratio of the mechanical parameter to the electrical parameter of the same type.

[0008] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, wherein the target value is the ratio, and the judgment module further includes: comparing the ratio with the target preset threshold, and if the ratio does not meet the target preset threshold, determining that the motor is in a heavy load state.

[0009] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and calculating the ratio of the ratio to a preset ratio, wherein the target value is the preset ratio. The judgment module further includes: comparing the preset ratio with the target value, and if the preset ratio does not meet the target value, determining that the motor is in the heavy load state.

[0010] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and calculating the difference of the ratio within a preset time period, wherein the target value is the difference. The judgment module further includes: comparing the difference with the target preset threshold, and if the difference does not meet the target preset threshold, determining that the motor is in the heavy load state.

[0011] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and calculating the slope of the ratio, wherein the target value is the slope, and the judgment module further includes: comparing the slope with the target preset threshold, and if the slope does not meet the target preset threshold, determining that the motor is in the heavy load state.

[0012] In some embodiments, the motor includes a first gear, a second gear, and a third gear with sequentially increasing output capabilities. The target preset threshold is the same when the motor is in the first gear, the second gear, and the third gear; or, the target preset threshold decreases sequentially when the motor is in the first gear, the second gear, and the third gear; or, the target preset threshold increases sequentially when the motor is in the first gear, the second gear, and the third gear.

[0013] In some embodiments, the target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters.

[0014] In some embodiments, the system further includes a control module, which is configured to adjust the mechanical or electrical parameters of the motor when the motor is in the heavy load state, so as to reduce the working efficiency of the motor until the motor is out of the heavy load state.

[0015] According to some embodiments of this disclosure, another aspect of this disclosure provides a method for detecting a heavy-load state, comprising: acquiring at least one mechanical parameter and at least one electrical parameter of a motor, wherein the mechanical parameter includes a speed parameter, a sector time parameter, or a torque parameter, and the electrical parameter includes a bus current parameter, a phase current parameter, a bus voltage parameter, a power parameter, a freewheeling time parameter, or a duty cycle parameter; processing the mechanical and electrical parameters of the motor according to a target calculation formula, and generating a target value, wherein the target calculation formula includes at least a ratio, a slope of the ratio, or a difference of the ratio; determining whether the motor is in a heavy-load state based on the target value and a target preset threshold, wherein if the target value does not meet the target preset threshold, the motor is determined to be in a heavy-load state, wherein the target preset threshold is correlated with the target calculation formula.

[0016] The technical solution provided in this disclosure has at least the following advantages: by acquiring the mechanical and electrical parameters of the motor through the acquisition module, it is convenient for the detection module to generate target values. The detection module processes the mechanical and electrical parameters of the motor according to the target calculation formula to obtain the target values, thereby making it easier for the judgment module to determine whether the motor is under heavy load. Furthermore, the ratio of mechanical parameters to electrical parameters can more easily provide feedback on whether the motor is under heavy load, and can simplify the calculation of the entire ratio, thereby freeing up the calculation capacity of the detection module. It also provides a more accurate way to determine whether the motor is under heavy load by using the ratio of mechanical parameters to electrical parameters. Attached Figure Description

[0017] One or more embodiments are illustrated by way of example with corresponding pictures in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Unless otherwise stated, the pictures in the accompanying drawings do not constitute a limitation on scale. In order to more clearly illustrate the technical solutions in the embodiments of this disclosure or the conventional technology, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A circuit diagram corresponding to a first type of electric work vehicle provided in an embodiment of this disclosure;

[0019] Figure 2 This is a circuit diagram corresponding to a second type of electric work vehicle provided in an embodiment of the present disclosure;

[0020] Figure 3 A module diagram corresponding to an embodiment of this disclosure is provided;

[0021] Figure 4A schematic diagram of sector timing provided for an embodiment of this disclosure;

[0022] Figure 5 A flowchart corresponding to the first type of electric work vehicle provided in an embodiment of this disclosure;

[0023] Figure 6 A flowchart corresponding to the second type of electric work vehicle provided in an embodiment of this disclosure;

[0024] Figure 7 A flowchart corresponding to a third type of electric work vehicle provided in an embodiment of this disclosure;

[0025] Figure 8 A flowchart corresponding to the fourth type of electric work vehicle provided in an embodiment of this disclosure;

[0026] Figure 9 A graph corresponding to the first type of electric work vehicle provided in an embodiment of this disclosure;

[0027] Figure 10 A graph corresponding to the second type of electric work vehicle provided in an embodiment of this disclosure;

[0028] Figure 11 A graph corresponding to the third type of electric work vehicle provided in an embodiment of this disclosure;

[0029] Figure 12 A graph corresponding to the fourth type of electric work vehicle provided in an embodiment of this disclosure;

[0030] Figure 13 A graph corresponding to the third type of electric work vehicle provided in an embodiment of this disclosure;

[0031] Figure 14 The graph corresponds to the fourth type of electric work vehicle provided in one embodiment of this disclosure. Detailed Implementation

[0032] As the background technology indicates, during the operation of current electric work vehicles, the accumulation of grass debris during mowing increases the load on the vehicle. This increased load causes a sudden surge in output power, while the power supply voltage remains relatively stable, resulting in a rapid increase in current. If the control module's protection current threshold is set too high or the delay time is too long, the power devices may burn out due to protection lag, exceeding their SOA (Safe Operating Area) for an extended period. The most typical cause is overcurrent damage. Even if the power devices are not damaged, the sudden current surge in stress on the motor itself is destructive, potentially leading to stator burnout or rotor magnet demagnetization over time. Conversely, if the controller sets a low protection current threshold or a short time, while the protection is more sensitive and the power devices are less likely to be damaged, it can easily cause shutdowns under such heavy load surges, severely impacting the user's experience. Furthermore, current methods for determining heavy load surges typically rely on a single parameter, leading to unstable and misjudgment results.

[0033] This disclosure provides an electric work vehicle. A data acquisition module collects the mechanical and electrical parameters of the motor, facilitating the generation of target values ​​by the detection module. The detection module processes the mechanical and electrical parameters of the motor according to the target calculation formula to obtain the target values. This allows the judgment module to determine whether the motor is under heavy load. Furthermore, the ratio of mechanical to electrical parameters provides easier feedback on whether the motor is under heavy load, and simplifies the calculation of the ratio, thus freeing up the detection module's computational power. This provides a more accurate way to determine whether the motor is under heavy load by analyzing the ratio of mechanical to electrical parameters.

[0034] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the embodiments of this disclosure to facilitate a better understanding of the disclosure. However, the technical solutions claimed in this disclosure can be implemented even without these technical details and various variations and modifications based on the following embodiments.

[0035] refer to Figures 1 to 3 , Figure 1 This is a first circuit diagram corresponding to an electric work vehicle provided in an embodiment of the present disclosure; Figure 2 This is a second circuit diagram corresponding to an electric work vehicle provided in one embodiment of the present disclosure; Figure 3 This is a module diagram corresponding to an embodiment of the present disclosure of an electric work vehicle.

[0036] In some embodiments, the electric work vehicle may include: motor 100.

[0037] The electric work vehicle may include: a data acquisition module 104, which is used to acquire at least one mechanical parameter and at least one electrical parameter of the motor 100. The mechanical parameters include speed parameters, sector time parameters or torque parameters, and the electrical parameters include bus current parameters, phase current parameters, bus voltage parameters, power parameters, freewheeling time parameters or duty cycle parameters.

[0038] The electric work vehicle may also include: a detection module 101, which is used to process the mechanical and electrical parameters of the motor 100 according to the target calculation formula and generate target values. The target calculation formula includes at least the ratio, the slope of the ratio, or the difference of the ratio.

[0039] The electric work vehicle may also include: a judgment module 102, which is used to determine whether the motor 100 is in a heavy load state based on the target value and the target preset threshold. If the target value does not meet the target preset threshold, it is determined that the motor 100 is in a heavy load state. The target preset threshold is related to the target calculation formula.

[0040] In this embodiment, the acquisition module 104 acquires the mechanical and electrical parameters of the motor 100, which facilitates the detection module 101 in generating target values. The detection module 101 processes the mechanical and electrical parameters of the motor 100 according to the target calculation formula to obtain the target values. This makes it easier for the judgment module to determine whether the motor 100 is under heavy load. By obtaining the target values ​​of the mechanical and electrical parameters, it is easier to provide feedback on whether the motor 100 is under heavy load. On the other hand, it simplifies the calculation of the entire ratio, thereby freeing up the calculation capacity of the detection module 101. Furthermore, the target values ​​of the mechanical and electrical parameters allow for a more accurate determination of whether the motor 100 is under heavy load.

[0041] In some embodiments, the motor 100 is used to drive the electric work vehicle. Taking the electric work vehicle as an example, the motor 100 can be used to drive the rotation of the cutter blade.

[0042] In some embodiments, the speed parameter includes: speed, speed difference, or slope of the speed curve; the sector time parameter includes: sector time, sector time difference, or slope of the sector time curve; the torque parameter includes: torque, torque difference, or slope of the torque curve; the bus current parameter includes: bus current, bus current difference, or slope of the bus current curve; the phase current parameter includes: phase current, phase current difference, or slope of the phase current curve; the bus voltage parameter includes: bus voltage, bus voltage difference, or slope of the bus voltage curve; the power parameter includes: power, power difference, or slope of the power curve; the freewheeling time parameter includes: freewheeling time, freewheeling time difference, or slope of the freewheeling time curve; the duty cycle parameter includes: duty cycle parameter, duty cycle parameter difference, or slope of the duty cycle parameter curve; and the target value is the ratio of mechanical parameters to electrical parameters of the same type.

[0043] It is understandable that the ratio of the same type here refers to the ratio of a specified parameter to another specified parameter, or the ratio of a difference to another difference, or the ratio of a slope to another slope. For example, the ratio of speed to bus current, or the ratio of the speed difference to the bus current difference, or the ratio of the slope of the speed curve to the slope of the bus current curve, etc. The ratio of mechanical parameter to electrical parameter can be mechanical parameter / electrical parameter, or electrical parameter / mechanical parameter.

[0044] The following will explain the various mechanical and electrical parameters.

[0045] In some embodiments, the rotational speed is: the rotational speed of motor 100 is sampled.

[0046] The speed difference is: the speed N obtained at the current moment. k Compared with the rotational speed N obtained at the previous moment k-1 The difference is used to obtain ΔN k The speed difference can be an absolute value, meaning the obtained ΔN k It is a positive number, which makes it easier to calculate the ratio later.

[0047] The slope of the rotational speed curve is: (The values ​​t0, t1, t2…t are obtained from the given information.) k Rotational speeds N0, N1, N2…N at time points k N0, N1, N2...N k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtN–Et*EN) / [Et 2 –(Et) 2 Where EtN is the expected value of the product of sampling time t and rotational speed, Et is the expected value of sampling time t, EN is the expected value of rotational speed, and Et 2 Let (Et) be the mathematical expectation of the square of the sampling time t. 2Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[N*∑(t*N)-∑t*∑N] / [N*∑t 2 -∑t*∑t], where N is a positive integer, * is the product of mathematical operations, Δt0, Δt1, ..., Δt k It represents the time difference between two adjacent moments.

[0048] refer to Figure 4 , Figure 4 This is a schematic diagram of sector timing provided in one embodiment of the present disclosure.

[0049] In some embodiments, the sector time can be: sampling the sector time of motor 100. It is understood that, taking motor 100 as an example of a three-phase brushless DC motor or a three-phase permanent magnet synchronous motor, one electrical cycle of a three-phase brushless DC motor or a three-phase permanent magnet synchronous motor is 360°, which is generally divided into 6 sectors, each sector being 60° electrical angle. Taking a square wave driven brushless DC motor as an example, the sectors are as follows: Figure 4 When the motor is running smoothly at 100°, the time of each sector of the 360° electrical cycle (Δt0, Δt1, Δt2, Δt3, Δt4, Δt5) is relatively close. However, when the load changes drastically, the sector time will also change abruptly.

[0050] The sector time difference is: the sector time S acquired at the current moment. k The sector time S obtained from the previous moment k-1 The difference is used to obtain ΔS k The sector time difference can be an absolute value, meaning that the obtained ΔS k It is a positive number, which makes it easier to calculate the ratio later.

[0051] The slope of the sector time curve is: (The values ​​t0, t1, t2…t are obtained.) k Sector times S0, S1, S2…S k S0, S1, S2...S k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtS-Et*ES) / [Et 2 -(Et) 2 Where EtS is the expected value of the product of sampling time t and sector time, Et is the expected value of sampling time t, ES is the expected value of sector time, and Et 2Let (Et) be the mathematical expectation of the square of the sampling time t. 2 Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[S*∑(t*S)-∑t*∑S] / [S*∑t 2 -∑t*∑t], where S is a positive integer, * is the product of mathematical operations, Δt0, Δt1, ..., Δt k It represents the time difference between two adjacent moments.

[0052] In some embodiments, the torque can be: sampling the torque of the motor 100.

[0053] The torque difference is: the torque A obtained at the current moment. k The torque A obtained at the previous moment k-1 The difference is used to obtain ΔA k The torque difference can be an absolute value, meaning the obtained ΔA... k It is a positive number, which makes it easier to calculate the ratio later.

[0054] The slope of the torque curve is: (The values ​​t0, t1, t2…t are obtained from the given information.) k Torques at time points A0, A1, A2…A k , A0, A1, A2...A k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtA-Et*EA) / [Et 2 -(Et) 2 Where EtA is the expected value of the product of sampling time t and torque, Et is the expected value of sampling time t, EA is the expected value of torque, Et2 is the expected value of the square of sampling time t, and (Et) 2 Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[A*∑(t*A)-∑t*∑A] / [A*∑t 2 -∑t*∑t], where A is a positive integer, * is the product of mathematical operations, Δt0, Δt1, ..., Δt k It represents the time difference between two adjacent moments.

[0055] In some embodiments, the bus current can be: Figure 2 The current flowing through Rs.

[0056] The bus current difference is: the bus current B obtained at the current moment. k Compared with the bus current B obtained at the previous moment k-1 The difference is used to obtain ΔB k The bus current difference can be an absolute value, meaning that the obtained ΔB k It is a positive number, which makes it easier to calculate the ratio later.

[0057] The slope of the bus current curve is: (The values ​​t0, t1, t2…t are obtained from the given information.) k Bus currents B0, B1, B2…B at time points k B0, B1, B2...B k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtB-Et*EB) / [Et 2 -(Et) 2 Where EtB is the expected value of the product of sampling time t and bus current, Et is the expected value of sampling time t, EB is the expected value of bus current, and Et 2 Let (Et) be the mathematical expectation of the square of the sampling time t. 2 Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[B*∑(t*B)-∑t*∑B] / [B*∑t 2 -∑t*∑t], where B is a positive integer, Δt0, Δt1, ..., Δt k It represents the time difference between two adjacent moments.

[0058] In some embodiments, the phase current of the motor 100 has alternating current characteristics. The phase current can be obtained by connecting current sensors to different output terminals of the motor 100 to sample the motor 100, or by connecting sampling resistors.

[0059] The phase current difference is: the phase current C obtained at the current moment. k The phase current C obtained at the previous moment k-1 The difference is used to obtain ΔC k The phase current difference can be an absolute value, meaning that the obtained ΔC k It is a positive number, which makes it easier to calculate the ratio later.

[0060] The slope of the phase current curve is: (The values ​​t0, t1, t2…t are obtained from the given information.) k Phase currents C0, C1, C2…C at time points k C0, C1, C2...C k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtC-Et*EC) / [Et 2 -(Et) 2 Where EtC is the expected value of the product of sampling time t and phase current, Et is the expected value of sampling time t, EC is the expected value of phase current, and Et 2 Let (Et) be the mathematical expectation of the square of the sampling time t. 2 Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[C*∑(t*C)-∑t*∑C] / [C*∑t2-∑t*∑t], where C is a positive integer, * is the product of mathematical operations, Δt0, Δt1……Δt k It represents the time difference between two adjacent moments.

[0061] In some embodiments, the bus voltage of the motor 100 can be the voltage between P+ and P-. The larger the load, the greater the relative voltage drop, and vice versa. In a battery-powered electric work vehicle, the larger the load, the more significant the drop in battery pack terminal voltage. Since terminal voltage corresponds to bus voltage, the bus voltage can reflect the battery pack terminal voltage. Here, battery pack can refer to the battery pack of the electric work vehicle.

[0062] The bus voltage difference is: the bus voltage D obtained at the current moment. k Compared with the bus voltage D obtained at the previous moment k-1 The difference is used to obtain ΔD k The bus voltage difference can be an absolute value, meaning that the obtained ΔD k It is a positive number, which makes it easier to calculate the ratio later.

[0063] The slope of the bus voltage curve is: (The values ​​t0, t1, t2…t are obtained from the given information.) k Bus voltages at times D0, D1, D2…D k D0, D1, D2...D k Perform linear fitting to obtain the corresponding curve slope k, and its formula (3) is: k=(EtD-Et*ED) / [Et 2-(Et) 2 Where EtD is the expected value of the product of sampling time t and bus voltage, Et is the expected value of sampling time t, ED is the expected value of bus voltage, and Et 2 Let (Et) be the mathematical expectation of the square of the sampling time t. 2 Let be the square of the mathematical expectation at sampling time t. Assume Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[D*∑(t*D)-∑t*∑D] / [D*∑t 2 -∑t*∑t], where D is a positive integer, * is the product of mathematical operations, Δt0, Δt1, ..., Δt k It represents the time difference between two adjacent moments.

[0064] In some embodiments, the power is: P = U * I * p, where U is the bus voltage on the DC input side, I is the bus current, and p is the power factor, where p on the DC side is always equal to 1; or, U is the phase voltage on the output side, I is the phase current, and p is the power factor, where p is less than or equal to 1.

[0065] The power difference and the slope of the power curve can be found in the description of the difference and slope above, and will not be repeated below.

[0066] In some embodiments, the freewheeling time can be directly tested by a timer. The timer is started at each commutation to calculate the freewheeling time. The freewheeling time can characterize the load size, where the larger the load, the longer the freewheeling time.

[0067] The difference in freewheeling time and the slope of the freewheeling time curve can be found in the description of the difference and slope above, and will not be repeated below.

[0068] In some embodiments, the duty cycle can be set according to actual conditions. The duty cycle can be tested by measuring the percentage of time the circuit is turned on during the entire circuit's operating cycle. The higher the duty cycle, the higher the rotational speed.

[0069] The duty cycle difference and the slope of the duty cycle curve can be found in the description of the difference and slope above, and will not be repeated below.

[0070] In some embodiments, the ratio of mechanical parameters to electrical parameters can be a ratio of the same type as the parameters mentioned above, such as the ratio between rotational speed and bus current, or the ratio between the difference in rotational speed and the difference in bus current, or the ratio between the slope of rotational speed and the slope of bus current, etc.

[0071] It is understandable that as load increases, speed decreases, sector time increases, torque decreases, bus current increases, phase current increases, bus voltage decreases, power increases, freewheeling time increases, and duty cycle decreases. In other words, speed and bus current are negatively correlated, speed and phase current are negatively correlated, speed and bus voltage are positively correlated, speed and power are negatively correlated, speed and freewheeling time are negatively correlated, and speed and duty cycle are positively correlated. Negative correlations make the extraction of target values ​​more obvious and easier, and can more easily indicate whether motor 100 is under heavy load. Positive correlations simplify the calculation process of detection module 101, freeing up its computational capacity. The ratios of other mechanical and electrical parameters can be found in the above description and will not be repeated below.

[0072] refer to Figures 1 to 3 , Figure 1 A circuit diagram of an electric work vehicle provided in an embodiment of this disclosure; Figure 2 A circuit diagram of a second type of electric work vehicle provided in an embodiment of this disclosure; Figure 3 This is a schematic diagram of a module corresponding to an electric work vehicle provided in an embodiment of this disclosure.

[0073] refer to Figure 1 The motor 100 may include a brushless motor, and the acquisition module 104 may include a back EMF acquisition module composed of several sampling resistors. The detection module 101 and the judgment module 102 may be integrated into the main control chip.

[0074] The electric work vehicle may also include multiple power devices MOSFET105.

[0075] refer to Figure 2 When it is necessary to collect current parameters, a current sampling module can be added. The current sampling module can include a sampling resistor and an operational amplifier.

[0076] refer to Figure 5 , Figure 9 and Figure 10 , Figure 5 The first flowchart provided in this embodiment of the present disclosure, wherein, open / closed-loop control according to the current control strategy of the motor 100 of the whole machine means: according to the acquired mechanical parameters and electrical parameters, and selecting a control method other than the acquired mechanical parameters and electrical parameters for control, taking the ratio between the speed and the current as an example, the motor 100 is controlled to be in a second operating state by controlling any parameter other than the speed and current, for example, by controlling the torque of the motor 100 to be fixed to a certain parameter, or by controlling the power to be fixed to a certain parameter.

[0077] Figure 9 It is a graph plotted by sampling current / speed as parameters. Figure 10 It is a curve plotted by sampling and drawing data using current / sector time as parameters. Figure 9 and Figure 10 It can be seen that when the ratio suddenly changes to the target preset threshold, it is determined to be in an overload state.

[0078] In some embodiments, the target calculation formula includes: calculating the ratio of mechanical parameters to electrical parameters of motor 100, where the target value is the ratio. The judgment module 102 further includes: comparing the ratio with a target preset threshold. If the ratio does not meet the target preset threshold, it is determined that motor 100 is in a heavy load state.

[0079] Taking current and speed as an example, determine the current ratio (current to speed ratio or speed to current ratio) R. k Is the ratio of current to speed greater than or equal to, or less than or equal to, a preset ratio threshold R? T If so, it is determined that the load has entered the heavy load operation area.

[0080] Furthermore, a time constraint can be added, specifying the current ratio (current to speed ratio or speed to current ratio) R within a preset ΔT time (e.g., 0.01 to 10 seconds). k The ratio of current to speed is greater than or equal to, or less than or equal to, a preset ratio threshold R. T If so, it is determined that the load has entered the heavy load operation area.

[0081] Furthermore, the aforementioned time constraint can be segmented, with X preset ΔT values. x Time, for example, setting X = 4, ΔT0 = 10 seconds, ΔT1 = 1 second, ΔT2 = 0.1 seconds, ΔT3 = 0.01 seconds, the current ratio (current to speed ratio or speed to current ratio) R within ΔT0 (10 seconds). k Greater than or equal to (current to speed ratio) or less than or equal to (speed to current ratio) R T0 And / or the current ratio (current to speed ratio or speed to current ratio) R within ΔT1 (1 second). k Greater than or equal to (current to speed ratio) or less than or equal to (speed to current ratio) R T1 And / or the current ratio (current to speed ratio or speed to current ratio) R within ΔT2 (0.1 seconds). k Greater than or equal to (current to speed ratio) or less than or equal to (speed to current ratio) R T2 And / or the current ratio (current to speed ratio or speed to current ratio) R within ΔT3 (0.01 seconds). k Greater than or equal to (current to speed ratio) or less than or equal to (speed to current ratio) RT3 If so, it is determined that the load has entered the heavy load operating area, R T0 ~R T3 Satisfy R T0 ≥R T1 ≥R T2 ≥R T3 , or R T0 ≤R T1 ≤R T2 ≤R T3 .

[0082] It should be noted that the preset ratio here can be a range with an upper and lower limit. The preset ratio can also be greater than or less than a certain value as the basis for judgment. For example, if the ratio of the acquired mechanical parameters to the electrical parameters is greater than a certain value, then motor 100 can be regarded as being in a heavy load state. If the ratio of the acquired mechanical parameters to the electrical parameters is less than a certain value, then motor 100 can be regarded as being in a heavy load state.

[0083] Continue to refer to Figure 5 , Figure 9 and Figure 10 In some embodiments, the motor 100 includes a first level, a second level, and a third level with sequentially increasing output capacity. The target preset threshold is the same when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold decreases sequentially when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold increases sequentially when the motor 100 is in the first level, the second level, and the third level.

[0084] If the target preset threshold is the same when motor 100 is in the first gear, the second gear, and the third gear—for example, the target preset threshold for motor 100 in the first gear is 0.5–0.8, the target preset threshold for motor 100 in the second gear is 0.5–0.8, and the target preset threshold for motor 100 in the third gear is 0.5–0.8—the ratios obtained when motor 100 is in the first gear, the ratios obtained when motor 100 is in the second gear, and the ratios obtained when motor 100 is in the third gear may be different, but all obtained ratios are compared with the same target preset threshold.

[0085] If the target preset threshold decreases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is highest in the first gear and lowest in the third gear, and the output capability is weakest in the first gear and strongest in the third gear.

[0086] Referring to Table 1 below for an example, if motor 100 is in the first gear, the target preset threshold is 0.5 to 0.8; if motor 100 is in the second gear, the target preset threshold is 0.8 to 1.2; and if motor 100 is in the third gear, the target preset threshold is 1.2 to 1.6. When determining the heavy load state, first determine which gear motor 100 is in. Taking a ratio of 0.9 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0087]

[0088]

[0089] Table 1

[0090] If the target preset threshold increases sequentially when the motor 100 is in the first gear, the second gear, and the third gear, that is, the target preset threshold is the lowest in the first gear and the highest in the third gear. The output capability of the first gear is the weakest and the output capability of the third gear is the strongest. In some other embodiments, the output capability of the first gear can also be the strongest and the output capability of the third gear can also be the weakest.

[0091] Referring to Table 2 below for examples, if motor 100 is in the first gear, the target preset threshold is 1.2 to 1.6; if motor 100 is in the second gear, the target preset threshold is 0.8 to 1.2; and if motor 100 is in the third gear, the target preset threshold is 0.5 to 0.8. When determining the heavy load state, first determine which gear motor 100 is in. Taking a ratio of 0.9 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0092] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 1.6 1.5 1.4 1.3 Second Tier 1.2 1.1 1.0 0.9 Third Tier 0.8 0.7 0.6 0.5

[0093] Table 2

[0094] Understandably, setting the target preset threshold to be the same when motor 100 is in the first, second, and third gears reduces the complexity of parameter setting and facilitates the judgment by module 102. Setting the target preset threshold to decrease sequentially when motor 100 is in the first, second, and third gears better reflects actual usage. For example, when motor 100 is in the third gear, its output capacity is strongest, meaning the user does not want motor 100 to stop running. Therefore, the target preset threshold can be set to be the lowest when motor 100 is in the third gear, making it more difficult to enter the heavy load state and preventing motor 100 from entering the second output state. Setting the target preset threshold to increase sequentially when motor 100 is in the first, second, and third gears ensures that the difficulty of judging the heavy load state is the same for each gear.

[0095] It should be noted that the above explanation addresses the situation where the ratio of the acquired mechanical parameters to electrical parameters decreases as the load increases. If the ratio of the acquired mechanical parameters to electrical parameters increases accordingly as the load increases, then setting the target preset threshold to decrease sequentially when motor 100 is in the first gear, the second gear, and the third gear can ensure that the difficulty of determining the heavy load state is the same for each gear. Setting the target preset threshold to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear can better reflect actual usage conditions.

[0096] Referring again to Tables 1 and 2, where ΔT0 to ΔT4 represent the sampling time intervals that decrease sequentially, ΔT0 can be 10s, ΔT1 can be 1s, ΔT2 can be 0.1s, and ΔT3 can be 0.01s. In some embodiments, a target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters. Taking speed as an example, when the speed is relatively high, the speed sampling frequency is much lower than the actual speed change frequency, resulting in large fluctuations in the obtained data. It is also possible that the actual speed change rate meets the application requirements, but the actual calculation and judgment fail to identify it. When the speed is relatively low, the speed sampling frequency is much higher than the frequency of the motor 100 speed filtering. The speed sampled at each moment may be the same, which wastes computing resources. Or, when the motor 100 speed fluctuates on a small time scale, it is easy to interfere with the calculation results and lead to misjudgment. Therefore, by setting the target preset threshold to a shorter sampling time interval and a larger target preset threshold to a longer sampling time interval, we can reduce the computing resources consumed and improve the accuracy of identifying whether the heavy load state has been entered.

[0097] It should be noted that the data in the table above is an example and represents the target preset threshold. It can be understood that the data in the table above is for illustrative purposes only and could be other data, and could also be values ​​in other ranges.

[0098] refer to Figure 6 , Figure 6 This is a second flowchart provided for an embodiment of the present disclosure.

[0099] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor 100, and calculating the ratio of the ratio to a preset ratio, wherein the target value is the ratio value. The judgment module 102 further includes: comparing the ratio value with a target preset threshold. If the ratio value does not meet the target preset threshold, it is determined that the motor 100 is in a heavy load state.

[0100] Understandably, taking the ratio of speed to current as an example, the obtained ratio is the ratio of the current speed to the current current, while the preset ratio is the ratio between the expected speed and the expected current under normal motor conditions. By comparing the ratio value with the target preset threshold, the judgment module 102 can also easily determine whether the motor 100 is under heavy load.

[0101] It should be noted that the preset ratio value here can be a range with an upper and lower limit. The preset ratio value can also be greater than or less than a certain value as the basis for judgment. For example, if the ratio of the obtained mechanical parameters to the electrical parameters to the preset ratio is greater than a certain value, then motor 100 can be regarded as being in a heavy load state. Similarly, if the ratio of the obtained mechanical parameters to the electrical parameters to the preset ratio is less than a certain value, then motor 100 can also be regarded as being in a heavy load state.

[0102] Continue to refer to Figure 6 In some embodiments, the motor 100 includes a first level, a second level, and a third level with sequentially increasing output capacity. The target preset threshold is the same when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold decreases sequentially when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold increases sequentially when the motor 100 is in the first level, the second level, and the third level.

[0103] If the target preset threshold is the same when motor 100 is in the first gear, the second gear, and the third gear—for example, the target preset threshold for motor 100 in the first gear is 40%–60%, the target preset threshold for motor 100 in the second gear is 40%–60%, and the target preset threshold for motor 100 in the third gear is 40%–60%—then the percentage values ​​obtained when motor 100 is in the first gear, the percentage values ​​obtained when motor 100 is in the second gear, and the percentage values ​​obtained when motor 100 is in the third gear may be different, but the obtained percentage values ​​are all compared with the same target preset threshold.

[0104] If the target preset threshold decreases sequentially when the motor 100 is in the first gear, the second gear, and the third gear, that is, the target preset threshold is the highest in the first gear and the lowest in the third gear, and the output capability is the weakest in the first gear and the strongest in the third gear. In other embodiments, the output capability can also be the strongest in the first gear and the weakest in the third gear.

[0105] Referring to Table 3 below for examples, if motor 100 is in the first gear, the target preset threshold is 30% to 50%; if motor 100 is in the second gear, the target preset threshold is 50% to 70%; and if motor 100 is in the third gear, the target preset threshold is 70% to 90%. When determining the heavy load state, first determine which gear motor 100 is in. Taking a ratio of 55% as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0106] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 45％ 40％ 35％ 30％ Second Tier 65％ 60％ 55％ 50％ Third Tier 85％ 80％ 75％ 70％

[0107] Table 3

[0108] If the target preset threshold increases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is lowest in the first gear and highest in the third gear, while the output capability is weakest in the first gear and strongest in the third gear.

[0109] Referring to Table 4 below for examples, if motor 100 is in the first gear, the target preset threshold is 70% to 90%; if motor 100 is in the second gear, the target preset threshold is 50% to 70%; and if motor 100 is in the third gear, the target preset threshold is 30% to 50%. When determining the heavy load state, first determine which gear motor 100 is in. Taking a ratio of 55% as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0110] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 85％ 80％ 75％ 70％ Second Tier 65％ 60％ 55％ 50％ Third Tier 45％ 40％ 35％ 30％

[0111] Table 4

[0112] Understandably, setting the target preset threshold to be the same when motor 100 is in the first, second, and third gears reduces the complexity of parameter setting and facilitates the judgment by module 102. Setting the target preset threshold to decrease sequentially when motor 100 is in the first, second, and third gears better reflects actual usage. For example, when motor 100 is in the third gear, its output capacity is strongest, meaning the user does not want motor 100 to stop running. Therefore, the target preset threshold can be set to be the lowest when motor 100 is in the third gear, making it more difficult to enter the heavy load state and preventing motor 100 from entering the second output state. Setting the target preset threshold to increase sequentially when motor 100 is in the first, second, and third gears ensures that the difficulty of judging the heavy load state is the same for each gear.

[0113] It should be noted that the above explanation addresses the situation where the ratio of the acquired mechanical parameters to the preset ratio decreases as the load increases. If the ratio of the acquired mechanical parameters to the preset ratio increases accordingly as the load increases, then setting the target preset threshold to decrease sequentially when motor 100 is in the first gear, the second gear, and the third gear can ensure that the difficulty of determining the heavy load state is the same for each gear. Setting the target preset threshold to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear can better reflect actual usage conditions.

[0114] Referring again to Tables 3 and 4, where ΔT0 to ΔT4 represent the sampling time intervals that decrease sequentially, ΔT0 can be 10s, ΔT1 can be 1s, ΔT2 can be 0.1s, and ΔT3 can be 0.01s. In some embodiments, a target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters. Taking speed as an example, when the speed is relatively high, the speed sampling frequency is much lower than the actual speed change frequency, resulting in large fluctuations in the obtained data. It is also possible that the actual speed change rate meets the application requirements, but the actual calculation and judgment fail to identify it. When the speed is relatively low, the speed sampling frequency is much higher than the frequency of the motor 100 speed filtering. The speed sampled at each moment may be the same, which wastes computing resources. Or, when the motor 100 speed fluctuates on a small time scale, it is easy to interfere with the calculation results and lead to misjudgment. Therefore, by setting the target preset threshold to a shorter sampling time interval and a larger target preset threshold to a longer sampling time interval, we can reduce the computing resources consumed and improve the accuracy of identifying whether the heavy load state has been entered.

[0115] It should be noted that the data in the table above is also an example and represents the target preset threshold. It can be understood that the data in the table above is for illustrative purposes and could be other data, and could also be values ​​in other ranges.

[0116] refer to Figure 7 , Figure 11 and Figure 12 , Figure 7 This is a third flowchart provided as an embodiment of the present disclosure. Figure 11 It is a curve plotted by sampling and generating data using the difference between current and rotational speed as parameters. Figure 12 It is a curve plotted by sampling and drawing the difference between current and sector time as parameters. Figure 11 and Figure 12 It can be seen that when the ratio suddenly changes to the target preset threshold, it is determined to be in an overload state.

[0117] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor 100, and calculating the difference of the ratio within a preset time period, with the target value being the difference. The judgment module 102 further includes: comparing the difference with a target preset threshold. If the difference does not meet the target preset threshold, it is determined that the motor 100 is in a heavy load state.

[0118] The same example is taken to illustrate the difference between the ratio of current to speed and the ratio of speed to current (the same idea and method are used to illustrate the difference between current to sector time and the ratio of sector time to current).

[0119] The ratio (current to speed ratio or speed to current ratio) R obtained at the current moment. k The ratio R obtained from the previous moment k-1 The difference is used to obtain ΔR. k If ΔR k Greater than or equal to the target preset threshold ΔR T If so, it is determined that the load has entered the heavy load operation area.

[0120] Furthermore, a time constraint can be added, specifying the difference ΔR between the current ratios within a preset time ΔT (e.g., 0.01 to 10 seconds). k Greater than or equal to the target preset threshold ΔR T If so, it is determined that the load has entered the heavy load operation area.

[0121] Furthermore, the aforementioned time constraint can be segmented, with X preset ΔT values. x For example, given X = 4, ΔT0 = 10 seconds, ΔT1 = 1 second, ΔT2 = 0.1 seconds, and ΔT3 = 0.01 seconds, the ratio R obtained at the current moment is used. k The ratio R to the previous ΔT0 (10 seconds) time point g The difference is used to obtain ΔR. kg , will R k The ratio R to the previous ΔT1 (1 second) time point h The difference is used to obtain ΔR. kh , will R k The ratio R to the previous ΔT2 (0.1 seconds) time point i The difference is used to obtain ΔR. ki , will R k The ratio R to the previous ΔT3 (0.01 seconds) time point j The difference is used to obtain ΔR. kj If ΔR kg Greater than or equal to the target preset threshold ΔR T0 , and / or ΔR kh Greater than or equal to the target preset threshold ΔR T1 , and / or ΔR ki Greater than or equal to the target preset threshold ΔR T2 , and / or ΔR kj Greater than or equal to the target preset threshold ΔR T3 If so, it is determined that the load has entered the heavy load operating region, ΔR T0 ~ΔR T3 Satisfying ΔR T0 ≥ΔR T1 ≥ΔR T2 ≥ΔR T3 .

[0122] Continue to refer to Figure 7In some embodiments, the motor 100 includes a first level, a second level, and a third level with sequentially increasing output capacity. The target preset threshold is the same when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold decreases sequentially when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold increases sequentially when the motor 100 is in the first level, the second level, and the third level.

[0123] If the target preset threshold is the same when motor 100 is in the first gear, the second gear, and the third gear—for example, the target preset threshold for motor 100 in the first gear is 0.1 to 0.3, the target preset threshold for motor 100 in the second gear is 0.1 to 0.3, and the target preset threshold for motor 100 in the third gear is 0.1 to 0.3—the differences obtained when motor 100 is in the first gear, the differences obtained when motor 100 is in the second gear, and the differences obtained when motor 100 is in the third gear may be different, but all the obtained differences are compared with the same target preset threshold.

[0124] If the target preset threshold decreases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is highest in the first gear and lowest in the third gear, and the output capability is weakest in the first gear and strongest in the third gear.

[0125] Referring to Table 5 below for examples, if motor 100 is in the first gear, the target preset threshold is 0.1 to 0.3; if motor 100 is in the second gear, the target preset threshold is 0.3 to 0.5; and if motor 100 is in the third gear, the target preset threshold is 0.5 to 0.7. When determining whether motor 100 is in a heavy load state, first determine which gear motor 100 is in. Taking a difference of 0.4 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0126] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 0.25 0.2 0.15 0.1 Second Tier 0.45 0.4 0.35 0.3 Third Tier 0.65 0.6 0.55 0.5

[0127] Table 5

[0128] If the target preset threshold increases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is lowest in the first gear and highest in the third gear, while the output capability is weakest in the first gear and strongest in the third gear.

[0129] Referring to Table 6 below for examples, if motor 100 is in the first gear, the target preset threshold is 0.5 to 0.7; if motor 100 is in the second gear, the target preset threshold is 0.3 to 0.5; and if motor 100 is in the third gear, the target preset threshold is 0.1 to 0.3. When determining the heavy load state, first determine which gear motor 100 is in. Taking a difference of 0.4 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0130] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 0.65 0.6 0.55 0.5 Second Tier 0.45 0.4 0.35 0.3 Third Tier 0.25 0.2 0.15 0.1

[0131] Table 6

[0132] Understandably, setting the target preset threshold to be the same when motor 100 is in the first, second, and third gears reduces the complexity of parameter setting and facilitates the judgment by the judgment module 102. Setting the target preset threshold to decrease sequentially when motor 100 is in the first, second, and third gears better reflects actual usage. For example, when motor 100 is in the third gear, its output capability is strongest, meaning the user would prefer that motor 100's output capability is not at its highest. It will stop running, so the target preset threshold can be set to be the smallest when motor 100 is in the third gear, making it more difficult to enter the heavy load state and preventing motor 100 from entering the second output state. The target preset threshold is set to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear, so that the difficulty of judging the heavy load state is the same for each gear. The difficulty here refers to the judgment standard for judging motor 100 to enter the heavy load state. In other words, the change range and degree of change are the same for the first gear, the second gear, and the third gear.

[0133] It should be noted that the above explanation addresses the situation where the ratio of the acquired mechanical parameters to electrical parameters decreases as the load increases. If the ratio of the acquired mechanical parameters to electrical parameters increases accordingly as the load increases, then setting the target preset threshold to decrease sequentially when motor 100 is in the first gear, the second gear, and the third gear can ensure that the difficulty of determining the heavy load state is the same for each gear. Setting the target preset threshold to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear can better reflect actual usage conditions.

[0134] Referring again to Tables 5 and 6, where ΔT0 to ΔT4 represent the sampling time intervals that decrease sequentially, ΔT0 can be 10s, ΔT1 can be 1s, ΔT2 can be 0.1s, and ΔT3 can be 0.01s. In some embodiments, a target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters. Taking speed as an example, when the speed is relatively high, the speed sampling frequency is much lower than the actual speed change frequency, resulting in large fluctuations in the obtained data. It is also possible that the actual speed change rate meets the application requirements, but the actual calculation and judgment fail to identify it. When the speed is relatively low, the speed sampling frequency is much higher than the frequency of the motor 100 speed filtering. The speed sampled at each moment may be the same, which wastes computing resources. Or, when the motor 100 speed fluctuates on a small time scale, it is easy to interfere with the calculation results and lead to misjudgment. Therefore, by setting the target preset threshold to a shorter sampling time interval and a larger target preset threshold to a longer sampling time interval, we can reduce the computing resources consumed and improve the accuracy of identifying whether the heavy load state has been entered.

[0135] It should be noted that the data in the table above is also an example and represents the target preset threshold. It can be understood that the data in the table above is for illustrative purposes and could be other data, and could also be values ​​in other ranges.

[0136] refer to Figure 8 , Figure 13 and Figure 14 , Figure 8 This is a fourth flowchart provided in one embodiment of the present disclosure. Figure 13 It is a curve plotted using current / speed as parameters and showing the slope. Figure 14 It is a curve plotted with the slope of the current / sector time as the parameter, which is obtained by sampling. Figure 13 and Figure 14 It can be seen that when the slope of the ratio curve suddenly changes to the target preset threshold, it is determined to be in an overload state.

[0137] In some embodiments, the target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor 100, and obtaining the slope of the curve of the ratio, with the target value being the slope. The judgment module 102 further includes: comparing the slope with a target preset threshold. If the slope does not meet the target preset threshold, it is determined that the motor 100 is in the heavy load state.

[0138] The slope of the current-to-speed and speed-to-current ratio curves is used as an example (the approach and method for the slope of the current-to-sector-time and sector-time-to-current ratio curves are the same). Obtain t0, t1, t2…t kThe ratios of time points R0, R1, R2…R k R0, R1, R2...R k Perform linear fitting to obtain the corresponding curve slope k, and its formula (15) is: k=(Eti-Et*Ei) / [Et 2 -(Et) 2 In the formula, Etr is the expected value of the product of sampling time t and the ratio, Et is the expected value of sampling time t, Er is the expected value of the ratio, and Et 2 Let (Et) be the mathematical expectation of the square of the sampling time t. 2 Let Δt0 be the square of the mathematical expectation at sampling time t, assuming Δt0 = t1 - t0, Δt1 = t2 - t1, ..., Δt k =t k+1 -t k To facilitate software calculations, it is generally designed as follows: Δt0 = Δt1 = ... = Δt k Therefore, the above formula can be simplified to: k=[n*Σ(t*r)-Σt*Σr] / [n*Σt 2 -Σt*Σt], where n is a positive integer. To further simplify the calculation process and reduce software computation overhead, n in the simplified formula above can be set to 2. m Where m is a positive integer, when m = 1, the above formula degenerates into the difference of the above ratios. When the slope k is greater than or equal to (the ratio of current to rotational speed), Figure 13 Chinese K IN ≥k INT The preset slope threshold k T Or less than or equal to (the ratio of rotational speed to current), Figure 13 Chinese K NI ≤k NIT The preset slope threshold k T This means that the load has entered the heavy load operation area.

[0139] Continue to refer to Figure 8 In some embodiments, the motor 100 includes a first level, a second level, and a third level with sequentially increasing output capacity. The target preset threshold is the same when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold decreases sequentially when the motor 100 is in the first level, the second level, and the third level; or, the target preset threshold increases sequentially when the motor 100 is in the first level, the second level, and the third level.

[0140] If the target preset threshold is the same when motor 100 is in the first gear, the second gear, and the third gear—for example, the target preset threshold is 1-3 when motor 100 is in the first gear, the target preset threshold is 1-3 when motor 100 is in the second gear, and the target preset threshold is 1-3 when motor 100 is in the third gear—the difference obtained when motor 100 is in the first gear, the difference obtained when motor 100 is in the second gear, and the difference obtained when motor 100 is in the third gear may be different, but all the obtained differences are compared with the same target preset threshold.

[0141] If the target preset threshold decreases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is highest in the first gear and lowest in the third gear, and the output capability is weakest in the first gear and strongest in the third gear.

[0142] Referring to Table 7 below for examples, if motor 100 is in the first gear, the target preset threshold is 1-3; if motor 100 is in the second gear, the target preset threshold is 3-5; and if motor 100 is in the third gear, the target preset threshold is 5-7. When determining whether motor 100 is in a heavy load state, first determine which gear motor 100 is in. Taking the difference case of 4 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0143] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 2.5 2 1.5 1 Second Tier 4.5 4 3.5 3 Third Tier 6.5 6 5.5 5

[0144] Table 7

[0145] If the target preset threshold increases sequentially when motor 100 is in the first gear, the second gear, and the third gear, that is to say, the target preset threshold is lowest in the first gear and highest in the third gear, while the output capability is weakest in the first gear and strongest in the third gear.

[0146] Referring to Table 8 below for examples, if motor 100 is in the first gear, the target preset threshold is 5-7; if motor 100 is in the second gear, the target preset threshold is 3-5; and if motor 100 is in the third gear, the target preset threshold is 1-3. When determining the heavy load state, first determine which gear motor 100 is in. Taking the difference case of 4 as an example, when motor 100 is in the first gear, it is determined that motor 100 is in a heavy load state; when motor 100 is in the second gear, it is determined that motor 100 is in a normal state; and when motor 100 is in the third gear, it is determined that motor 100 is in a heavy load state.

[0147] <![CDATA[ΔT0]]> <![CDATA[ΔT1]]> <![CDATA[ΔT2]]> <![CDATA[ΔT3]]> First Tier 6.5 6 5.5 5 Second Tier 4.5 4 3.5 3 Third Tier 2.5 2 1.5 1

[0148] Table 8

[0149] Understandably, setting the target preset threshold to be the same when motor 100 is in the first, second, and third gears reduces the complexity of parameter setting and facilitates the judgment by the judgment module 102. Setting the target preset threshold to decrease sequentially when motor 100 is in the first, second, and third gears better reflects actual usage. For example, when motor 100 is in the third gear, its output capability is strongest, meaning the user would prefer that motor 100's output capability is not at its highest. It will stop running, so the target preset threshold can be set to be the smallest when motor 100 is in the third gear, making it more difficult to enter the heavy load state and preventing motor 100 from entering the second output state. The target preset threshold is set to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear, so that the difficulty of judging the heavy load state is the same for each gear. The difficulty here refers to the judgment standard for judging motor 100 to enter the heavy load state. In other words, the change range and degree of change are the same for the first gear, the second gear, and the third gear.

[0150] It should be noted that the above explanation addresses the situation where the ratio of the acquired mechanical parameters to electrical parameters decreases as the load increases. If the ratio of the acquired mechanical parameters to electrical parameters increases accordingly as the load increases, then setting the target preset threshold to decrease sequentially when motor 100 is in the first gear, the second gear, and the third gear can ensure that the difficulty of determining the heavy load state is the same for each gear. Setting the target preset threshold to increase sequentially when motor 100 is in the first gear, the second gear, and the third gear can better reflect actual usage conditions.

[0151] Referring again to Tables 7 and 8, where ΔT0 to ΔT4 represent the sampling time intervals that decrease sequentially, ΔT0 can be 10s, ΔT1 can be 1s, ΔT2 can be 0.1s, and ΔT3 can be 0.01s. In some embodiments, a target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters. Taking speed as an example, when the speed is relatively high, the speed sampling frequency is much lower than the actual speed change frequency, resulting in large fluctuations in the obtained data. It is also possible that the actual speed change rate meets the application requirements, but the actual calculation and judgment fail to identify it. When the speed is relatively low, the speed sampling frequency is much higher than the frequency of the motor 100 speed filtering. The speed sampled at each moment may be the same, which wastes computing resources. Or, when the motor 100 speed fluctuates on a small time scale, it is easy to interfere with the calculation results and lead to misjudgment. Therefore, by setting the target preset threshold to a shorter sampling time interval and a larger target preset threshold to a longer sampling time interval, we can reduce the computing resources consumed and improve the accuracy of identifying whether the heavy load state has been entered.

[0152] It should be noted that the data in the table above is also an example and represents the target preset threshold. It can be understood that the data in the table above is for illustrative purposes and could be other data, and could also be values ​​in other ranges.

[0153] In some embodiments, the detection module 101 further includes filtering the obtained ratio of mechanical parameters and electrical parameters before acquiring the slope of the ratio of mechanical parameters and electrical parameters.

[0154] In some embodiments, the filtering methods mainly include: fixed window filtering, sliding window filtering, arithmetic mean filtering, extreme value removal averaging filtering, median filtering, etc. Different algorithms can be combined, such as fixed window arithmetic mean filtering, sliding window median filtering, etc., so that the above ratios R0, R1, R2...R k The values ​​are obtained after filtering. Thus, when using a fixed-window filtering series method, Δt0, Δt1, Δt2…Δt… k The value is the sampling interval of X ratios. For example, if a ratio is acquired every 1ms, and X is preset to 8, then the filtered value will be calculated every 8ms, Δt0 = Δt1 = Δt2 = Δt k =8ms; When using the sliding window filtering method, under the same preset conditions, then Δt0 = Δt1 = Δt2 = Δt k =1ms. After each fixed-window filtering or sliding-window filtering is completed, the slope k is calculated using the method described above for obtaining the slope of the ratio, which is the first derivative of the ratio with respect to unit time.

[0155] Understandably, the fixed window filtering method involves acquiring a ratio every x ms, for a total of n values. For example, acquiring a ratio every 1 ms yields 8 ratios, with each acquisition grouping the ratios into sets of 8. The sliding window filtering method involves acquiring a ratio every x ms, for a total of n ratios, but the next set of ratios consists of the last n-1 ratios of the previous set combined with the newly acquired ratios. For example, acquiring a ratio every 1 ms yields 8 ratios, and the ratio acquired in the next 1 ms, along with the last 7 ratios from the previous set, forms a new resistance value. The arithmetic mean filtering method involves acquiring the arithmetic mean of each set of ratios. The extreme value removal average filtering method involves acquiring each set of ratios and then removing the n maximum and n minimum values. The median filtering method involves acquiring each set of ratios and then taking the median of each set of ratios.

[0156] Furthermore, if the ratio range of motor 100 is relatively large, Δt0, Δt1, Δt2…Δt k The value can be dynamically adjusted based on the current motor 100 ratio, because if Δt0, Δt1, Δt2…Δt k If the value is too small, when the motor 100 ratio is relatively low, the sampling frequency of the ratio is much higher than the filtering frequency of the motor 100 ratio. The ratio sampled at each moment may be the same, which wastes computing resources unnecessarily. Or, when the motor 100 ratio fluctuates at small time scales, it can easily interfere with the calculation results and lead to misjudgment. If Δt0, Δt1, Δt2…Δt k If the value is too large, when the motor 100 ratio is relatively high, the ratio sampling frequency is much lower than the actual ratio change frequency, resulting in large fluctuations in the obtained data. Alternatively, the actual ratio change rate may already meet the application requirements, but the actual calculation and judgment fail to recognize it. Therefore, Δt0, Δt1, Δt2…Δt k The adjustment rule is that when the ratio is high, the time interval is small, and when the ratio is low, the time interval is large. There are three ways to adjust this time interval. The first is to adjust the 1ms ratio sampling interval, for example, to 0.5ms or 2ms. In this way, under the fixed window filtering method, Δt0 = Δt1 = Δt2 = Δt k =4ms or 16ms, under the sliding window filtering series of methods, Δt0 = Δt1 = Δt2 = Δt k =0.5ms or 2ms; the second method is to adjust the window length (number of sampling points X), for example, to X=4 or X=16, so that under the fixed window filtering series method, Δt0=Δt1=Δt2=Δt k =4ms or 16ms, under the sliding window filtering series of methods, Δt0 = Δt1 = Δt2 = Δt kIt still equals 1ms; the third method is to simultaneously adjust the ratio sampling interval and the window length (number of sampling points X). Additionally, because the ratio decreases rapidly when the load changes abruptly, this process will not adjust Δt0, Δt1, Δt2…Δt. k The ratio will only be adjusted after it has stabilized over a period of time.

[0157] Furthermore, after each fixed-window or sliding-window filtering step, the slope is obtained using the aforementioned method, thus yielding a set of k0, k1, k2…k k For k0, k1, k2...k k Next, perform linear fitting to obtain the corresponding slope k', which is given by the formula: k'=(Etk-Et*Ek) / [Et] 2 -(Et) 2 In the formula: Etk represents the expected value of the ratio slope at time t for each acquisition, Et represents the expected value of the ratio slope at time t for each acquisition, and Ek represents the expected value of the ratio slope. 2 Let (Et) be the mathematical expectation of the square of the slope of the ratio at each time t. 2 It is the square of the mathematical expectation at sampling time t.

[0158] Since each time k0, k1, k2...k are obtained, k The time intervals are equal, so Δt'0, Δt'1, Δt'2…Δt' k They are also equal. Therefore, the above formula can be simplified to: k'=[n'*Σ(t*k)-Σt*Σk] / [n'*Σt 2 -Σt*Σt], where n' is a positive integer. To further simplify the calculation process and reduce software computation overhead, n' in the simplified formula above can be set to 2. m’ m' is a positive integer. The slope k' is greater than or equal to the ratio of current to speed, or less than or equal to the preset slope threshold k'. T This indicates that the load has entered the heavy-load operating region. Here, the slope k' is the second derivative of the ratio with respect to unit time.

[0159] It should be noted that the above descriptions are based on one mechanical parameter and one electrical parameter of the motor. In reality, multiple mechanical parameters and multiple electrical parameters of the motor can be collected by the acquisition module, and the detection module can also compare multiple mechanical parameters and multiple electrical parameters.

[0160] refer to Figure 1 and Figure 2In some embodiments, the electric work vehicle may further include a control module 103. The control module 103 is used to adjust the mechanical or electrical parameters of the motor 100 when the motor 100 is under heavy load, so as to reduce the working efficiency of the motor 100 until the motor 100 is out of the heavy load state. The control module 103 can control the mechanical or electrical parameters of the motor 100, thereby preventing the motor 100 from stopping and also preventing damage to the components in the electric work vehicle. This improves the reliability of the electric work vehicle while enhancing user comfort. Taking the control module 103 controlling the speed of the motor 100 as an example, when the judgment module 102 determines that the motor 100 is under heavy load, it reduces the speed of the motor 100 to prevent the motor 100 from continuing to work at the initial speed and to prevent damage to the components in the electric work vehicle.

[0161] It should be noted that the work efficiency here can refer to the mowing capacity of the electric work vehicle. Mowing capacity refers to the weight of grass that can be cut per unit time, or the area of ​​lawn that can be mowed per unit time, etc.

[0162] In some embodiments, the control module 103 may be integrated with the detection module 101 and the judgment module 102 in the same chip.

[0163] In some embodiments, the mechanical or electrical parameters of the motor 100 adjusted by the control module 103 are different from those of the mechanical and electrical parameters acquired by the acquisition module 104, so as to avoid mutual interference between the control module 103 and the acquisition module 104.

[0164] In this embodiment, the acquisition module 104 acquires the mechanical and electrical parameters of the motor 100, which facilitates the detection module 101 in generating target values. The detection module 101 processes the mechanical and electrical parameters of the motor 100 according to the target calculation formula to obtain the target values. This makes it easier for the judgment module to determine whether the motor 100 is under heavy load. By obtaining the target values ​​of the mechanical and electrical parameters, it is easier to provide feedback on whether the motor 100 is under heavy load. On the other hand, it simplifies the calculation of the entire ratio, thereby freeing up the calculation capacity of the detection module 101. Furthermore, the target values ​​of the mechanical and electrical parameters allow for a more accurate determination of whether the motor 100 is under heavy load.

[0165] Another embodiment of this disclosure also provides a method for detecting a heavy-load state. This detection method can be implemented by an electric work vehicle in all or some of the above embodiments. The following will describe the method for detecting a heavy-load state provided by another embodiment of this disclosure. It should be noted that the same or corresponding parts of the foregoing embodiments can be referred to the corresponding descriptions of the foregoing embodiments, and will not be repeated below.

[0166] In some embodiments, the overload state detection method provided in this disclosure may include:

[0167] Collect at least one mechanical parameter and at least one electrical parameter of the motor. The mechanical parameters include speed parameters, sector time parameters or torque parameters, and the electrical parameters include bus current parameters, phase current parameters, bus voltage parameters, power parameters, freewheeling time parameters or duty cycle parameters.

[0168] The heavy-load state detection method provided in this embodiment may further include: processing the mechanical and electrical parameters of the motor according to a target calculation formula, and generating a target value. The target calculation formula includes at least a ratio, the slope of the ratio, or the difference of the ratio.

[0169] The method for detecting overload state provided in this embodiment may further include: determining whether the motor is under overload state based on a target value and a target preset threshold; if the target value does not meet the target preset threshold, determining that the motor is under overload state, wherein the target preset threshold is related to the target calculation formula.

[0170] This embodiment of the disclosure collects the mechanical and electrical parameters of the motor to generate target values. By processing the mechanical and electrical parameters of the motor according to the target calculation formula, the target values ​​are obtained. This makes it easier to determine whether the motor is under heavy load. Furthermore, the ratio of mechanical parameters to electrical parameters can more easily provide feedback on whether the motor is under heavy load, and can simplify the calculation of the entire ratio. This provides a more accurate way to determine whether the motor is under heavy load by using the ratio of mechanical parameters to electrical parameters.

[0171] Those skilled in the art will understand that the above embodiments are specific examples of implementing this disclosure, and in practical applications, various changes in form and detail may be made without departing from the spirit and scope of the embodiments of this disclosure. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the embodiments of this disclosure; therefore, the scope of protection of the embodiments of this disclosure should be determined by the scope defined in the claims.

Claims

1. An electric work vehicle, characterized in that, include: Electric motor; The acquisition module is used to acquire at least one mechanical parameter and at least one electrical parameter of the motor. The mechanical parameters include speed parameters, sector time parameters, or torque parameters. The electrical parameters include bus current parameters, phase current parameters, bus voltage parameters, power parameters, freewheeling time parameters, or duty cycle parameters. The detection module is used to process the mechanical and electrical parameters of the motor according to the target calculation formula and generate target values. The target calculation formula is used to calculate at least the ratio, the slope of the ratio, or the difference of the ratio. The judgment module is used to determine whether the motor is in a heavy load state based on the target value and the target preset threshold. If the target value does not meet the target preset threshold, the motor is determined to be in a heavy load state. The target preset threshold is related to the target calculation formula. The speed parameters include: speed, speed difference, or slope of the speed curve; the sector time parameters include: sector time, sector time difference, or slope of the sector time curve; the torque parameters include: torque, torque difference, or slope of the torque curve; the bus current parameters include: bus current, bus current difference, or slope of the bus current curve; the phase current parameters include: phase current, phase current difference, or slope of the phase current curve; the bus voltage parameters include: bus voltage, bus voltage difference, or slope of the bus voltage curve; the power parameters include: power, power difference, or slope of the power curve; the freewheeling time parameters include: freewheeling time, freewheeling time difference, or slope of the freewheeling time curve; the duty cycle parameters include: duty cycle parameters, duty cycle parameter difference, or slope of the duty cycle parameter curve; and the target value is the ratio of the mechanical parameters to the electrical parameters of the same type.

2. The electric work vehicle according to claim 1, characterized in that, The target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, wherein the target value is the ratio. The judgment module further includes: comparing the ratio with the target preset threshold. If the ratio does not meet the target preset threshold, the motor is determined to be in a heavy load state.

3. The electric work vehicle according to claim 1, characterized in that, The target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and calculating the ratio of the ratio to a preset ratio, wherein the target value is the preset ratio. The judgment module further includes: comparing the preset ratio with the target threshold, and if the preset ratio does not meet the target threshold, determining that the motor is in the heavy load state.

4. The electric work vehicle according to claim 1, characterized in that, The target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and calculating the difference of the ratio within a preset time period, wherein the target value is the difference. The judgment module further includes: comparing the difference with the target preset threshold, and if the difference does not meet the target preset threshold, determining that the motor is in the heavy load state.

5. The electric work vehicle according to claim 1, characterized in that, The target calculation formula includes: calculating the ratio of the mechanical parameters to the electrical parameters of the motor, and obtaining the slope of the curve of the ratio, wherein the target value is the slope. The judgment module further includes: comparing the slope with the target preset threshold, and if the slope does not meet the target preset threshold, determining that the motor is in the heavy load state.

6. The electric work vehicle according to any one of claims 2 to 5, characterized in that, The motor includes a first gear, a second gear, and a third gear with sequentially increasing output capabilities. The target preset threshold is the same when the motor is in the first gear, the second gear, and the third gear; or, the target preset threshold decreases sequentially when the motor is in the first gear, the second gear, and the third gear; or, the target preset threshold increases sequentially when the motor is in the first gear, the second gear, and the third gear.

7. The electric work vehicle according to claim 6, characterized in that, The target preset threshold is determined based on the sampling time, and the shorter the sampling time interval, the smaller the target preset threshold. The sampling time interval is the time interval between acquiring two adjacent mechanical parameters or two adjacent electrical parameters.

8. The electric work vehicle according to claim 1, characterized in that, Also includes: A control module is used to adjust the mechanical or electrical parameters of the motor when the motor is in the heavy load state, so as to reduce the working efficiency of the motor until the motor is out of the heavy load state.

9. A method for detecting overload conditions, characterized in that, include: The motor acquires at least one mechanical parameter and at least one electrical parameter. The mechanical parameter includes speed parameter, sector time parameter, or torque parameter. The electrical parameter includes bus current parameter, phase current parameter, bus voltage parameter, power parameter, freewheeling time parameter, or duty cycle parameter. According to the target calculation formula, the mechanical and electrical parameters of the motor are processed and target values ​​are generated. The target calculation formula is used at least to calculate the ratio, the slope of the ratio, or the difference of the ratio. The motor is determined to be under heavy load based on the target value and the target preset threshold. If the target value does not meet the target preset threshold, the motor is determined to be under heavy load. The target preset threshold is related to the target calculation formula. The speed parameters include: speed, speed difference, or slope of the speed curve; the sector time parameters include: sector time, sector time difference, or slope of the sector time curve; the torque parameters include: torque, torque difference, or slope of the torque curve; the bus current parameters include: bus current, bus current difference, or slope of the bus current curve; the phase current parameters include: phase current, phase current difference, or slope of the phase current curve; the bus voltage parameters include: bus voltage, bus voltage difference, or slope of the bus voltage curve; the power parameters include: power, power difference, or slope of the power curve; the freewheeling time parameters include: freewheeling time, freewheeling time difference, or slope of the freewheeling time curve; the duty cycle parameters include: duty cycle parameters, duty cycle parameter difference, or slope of the duty cycle parameter curve; and the target value is the ratio of the mechanical parameters to the electrical parameters of the same type.

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