CN111186308B - Electric vehicle driving torque distribution method and device and computer equipment - Google Patents

Electric vehicle driving torque distribution method and device and computer equipment Download PDF

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CN111186308B
CN111186308B CN201911424919.2A CN201911424919A CN111186308B CN 111186308 B CN111186308 B CN 111186308B CN 201911424919 A CN201911424919 A CN 201911424919A CN 111186308 B CN111186308 B CN 111186308B
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torque
motor
objective function
distribution coefficient
constraint range
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CN111186308A (en
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张昕睿
段捷
江清华
林钦鸿
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Hechuang Automotive Technology Co Ltd
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Hechuang Automotive Technology Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B60L2240/423—Torque
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

Abstract

The invention relates to a method, a device, computer equipment and a storage medium for distributing driving torque of an electric automobile. The method and the device can restrict the range of the torque distribution coefficients, reduce the calculated amount, avoid the extreme of the torque distribution mode, calculate the optimal torque distribution coefficient in each sub-restriction range, shorten the calculation time and realize the effect of optimally distributing the torque for economy and stability.

Description

Electric vehicle driving torque distribution method and device and computer equipment
Technical Field
The invention relates to the technical field of automobiles, in particular to a method and a device for distributing driving torque of an electric automobile, computer equipment and a computer readable storage medium.
Background
With the continuous deterioration of the environment and the rapid shortage of energy, various products using clean energy are developing at an increasing speed, and countries in the world make subsidies for the products, wherein an electric vehicle is one of the products using clean energy, and the electric vehicle is used as a new energy vehicle, and has the advantages of no pollution, low noise, high energy efficiency, energy diversification, convenience in maintenance and the like. The electric automobile driven by the double motors can improve the working efficiency of the whole automobile, so that the endurance mileage is improved.
The electric automobile driven by double motors usually needs to distribute the torque of each motor, and the current motor torque distribution method mainly comprises the distribution based on rules, the distribution based on an online optimization function and the distribution based on an offline optimization function, wherein the distribution calculation amount based on the rules is small, but the potential of a driving system cannot be fully exerted, and the economical and stable torque distribution cannot be realized; the allocation based on the online optimization function is usually huge in calculation amount and difficult to apply to actual engineering; based on the distribution of the offline optimization function, the calculation amount is small, but the influence of the actual running condition of the vehicle on the torque distribution is not considered.
Therefore, the current torque distribution method for the two motors has the defect that stable and economical torque distribution cannot be realized.
Disclosure of Invention
Based on this, it is necessary to provide a torque distribution device that can solve the technical problem of the conventional technology that cannot distribute torque stably and economically.
A method of driving torque in an electric vehicle including a front motor and a rear motor, the method comprising the steps of:
acquiring a constraint range of a torque distribution coefficient; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained through the total required torque, the front motor torque and the rear motor torque of the electric automobile;
dividing the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges;
solving an optimization objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimization objective function to be minimum; the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be optimal;
and obtaining the torque required by the front motor and the torque required by the rear motor of the electric automobile according to the total required torque and the target torque distribution coefficient.
In one embodiment, the obtaining of the constrained range of torque distribution coefficients comprises:
acquiring a first constraint range, wherein the first constraint range is obtained according to the external motor characteristics of the electric automobile at the current moment and the total required torque at the current moment;
acquiring a second constraint range, wherein the second constraint range is obtained according to a torque distribution coefficient of the electric automobile at the last preset moment, a total required torque at the last preset moment and a vehicle speed at the last preset moment;
and obtaining the constraint range of the torque distribution coefficient according to the first constraint range and the second constraint range.
In one embodiment, the obtaining the first constraint range includes:
acquiring a difference value between the total required torque at the current moment and the external characteristic torque of the rear motor at the current moment;
comparing the difference value with 0 to obtain the maximum value;
acquiring the sum of the external characteristic torque of the front motor at the current moment and the external characteristic torque of the rear motor at the current moment as the total external characteristic torque of the motor at the current moment;
acquiring a first minimum value between the total required torque at the current moment and the total external motor characteristic torque at the current moment;
acquiring the ratio of the maximum value to the first minimum value as the minimum value of the first constraint range;
acquiring a second minimum value between the external characteristic torque of the front motor at the current moment and the total required torque at the current moment;
acquiring the ratio of the second minimum value to the first minimum value as the maximum value of the first constraint range;
determining the first constraint range according to the minimum value of the first constraint range and the maximum value of the first constraint range;
the obtaining of the second constraint range includes:
subtracting a first preset value from the actual torque distribution coefficient at the last preset moment to obtain a preselected minimum value; the first preset value is inversely proportional to the acceleration of the electric vehicle;
acquiring the maximum value between the preselected minimum value and 0 as the minimum value of the second constraint range;
adding a second preset value to the actual torque distribution coefficient at the last preset moment to obtain a preselected maximum value; the second preset value is inversely proportional to the acceleration of the electric vehicle;
acquiring a minimum value between the preselected maximum value and 1 as a maximum value of the second constraint range;
determining the second constraint range according to the minimum value of the second constraint range and the maximum value of the second constraint range;
the obtaining of the constraint range of the torque distribution coefficient according to the first constraint range and the second constraint range includes:
and acquiring the intersection of the first constraint range and the second constraint range to obtain the constraint range of the torque distribution coefficient.
In one embodiment, before solving the optimization objective function according to the torque distribution coefficient in each of the sub-constraint ranges and the preset iterative algorithm, the method includes:
acquiring a first optimization objective function; the first optimization objective function is a function for calculating an axle load distribution optimal value of the electric automobile;
acquiring a second optimization objective function; the second optimization objective function is a function for calculating the optimal value of the total motor efficiency of the electric automobile;
obtaining an influence parameter of the second optimization objective function; the influence parameter is used for expressing the influence proportion of the second optimization objective function on the optimization objective function;
and determining the optimization objective function according to the first optimization objective function, the second optimization objective function and the influence parameters.
In one embodiment, the obtaining a first optimization objective function includes:
obtaining the first optimization objective function according to the front axle longitudinal force, the rear axle longitudinal force, the front axle load and the rear axle load of the electric automobile;
the obtaining a second optimization objective function includes:
determining a first efficiency function according to the front motor efficiency, the front motor torque and the front motor rotating speed of the electric automobile;
determining a second efficiency function according to the rear motor efficiency, the rear motor torque and the rear motor rotating speed of the electric automobile;
and obtaining the second optimization objective function according to the first efficiency function, the second efficiency function and the total required torque.
In an embodiment, the solving an optimized objective function according to the torque distribution coefficient in each of the sub-constraint ranges and a preset iterative algorithm to obtain a target torque distribution coefficient that minimizes an output value of the optimized objective function includes:
taking a first torque distribution coefficient which is a first preset value away from a minimum value in the sub-constraint range as a first input value of the optimization objective function;
taking a second torque distribution coefficient which is a second preset value away from the minimum value in the sub-constraint range as a second input value of the optimization objective function;
inputting the first input value and the second input value into the optimization objective function respectively to obtain a corresponding first output value and a corresponding second output value;
according to the first output value and the second output value, adjusting the sub-constraint range to enable the sub-constraint range to be adjusted to an input value corresponding to the smaller output value of the first output value and the second output value;
returning to performing the step of taking a first torque distribution coefficient which is a first preset value away from a minimum value in the sub-constraint range as a first input value of the optimization objective function, and stopping adjusting the sub-constraint range until a preset condition is reached; the preset condition is determined according to the sizes of the first output value and the second output value, the output value of the second optimization objective function, the output value of the first optimization objective function or the iteration times;
taking the average value of the first input value and the second input value as the optimal torque distribution coefficient corresponding to the sub-constraint range;
and selecting the optimal torque distribution coefficient which enables the output value of the optimization objective function to be minimum from the optimal torque distribution coefficients corresponding to the sub-constraint ranges as a target torque distribution coefficient.
In one embodiment, the preset condition includes at least one of:
the interval length of the adjusted sub-constraint range is smaller than a first threshold;
the output value of the first optimization objective function is smaller than a second threshold value;
the output value of the second optimization objective function is smaller than a third threshold value;
the number of iterations reaches a fourth threshold.
In one embodiment, the obtaining the torque required by the front motor and the torque required by the rear motor of the electric vehicle according to the total required torque and the target torque distribution coefficient includes:
obtaining a front motor expected torque and a rear motor expected torque of the electric automobile according to a motor driving torque calculation function and the target torque distribution coefficient; the motor driving torque calculation function is obtained according to the torque distribution coefficient and the total required torque;
when the expected torque of the front motor and the expected torque of the rear motor are both within a preset range, determining that the expected torque of the front motor and the expected torque of the rear motor are respectively the torque required by the front motor and the torque required by the rear motor;
when the expected torque of the front motor or the expected torque of the rear motor is out of a preset range, the expected torque of the front motor or the expected torque of the rear motor is adjusted to be within the preset range, and the torque required by the front motor and the torque required by the rear motor are obtained according to the adjusted expected torque of the front motor and the adjusted expected torque of the rear motor.
An electric vehicle drive torque distribution apparatus, the electric vehicle including a front motor and a rear motor, the apparatus comprising:
the acquisition module is used for acquiring a constraint range of the torque distribution coefficient; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained through the total required torque, the front motor torque and the rear motor torque of the electric automobile;
the dividing module is used for dividing the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges;
the calculation module is used for solving an optimized objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimized objective function to be minimum; the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be optimal;
and the distribution module is used for obtaining the torque required by the front motor and the torque required by the rear motor of the electric automobile according to the total required torque and the target torque distribution coefficient.
A computer device comprising a processor and a memory, the memory storing a computer program which, when executed by the processor, implements an electric vehicle drive torque distribution method as described above.
A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the electric vehicle drive torque distribution method as described above.
According to the electric vehicle driving torque distribution method, the electric vehicle driving torque distribution device, the computer equipment and the storage medium, the torque distribution coefficient constraint range is divided into a plurality of sub-constraint ranges by obtaining the constraint range of the torque distribution coefficient, the optimization objective function is solved in each sub-constraint range according to the torque distribution coefficient and the preset iterative algorithm, the objective torque distribution coefficient enabling the output value of the optimization objective function to be minimum is obtained, the torque distribution coefficient enabling the stability and the economy of an electric vehicle to be optimal is obtained, and the torque required by a front motor of the electric vehicle and the torque required by a rear motor of the electric vehicle are obtained according to the objective torque distribution coefficient and the total required torque. Compared with the traditional torque distribution method, the method and the device have the advantages that the range of the torque distribution coefficient can be constrained during optimization, the calculated amount is reduced, the extreme torque distribution mode is avoided, the optimal torque distribution coefficient can be calculated in each sub-constraint range, the occurrence of local optimal solution is avoided, the calculation time is shortened, and the effect of optimally distributing the torque with economy and stability is achieved.
Drawings
FIG. 1 is a schematic flow chart of an electric vehicle driving torque distribution method according to an embodiment;
FIG. 2 is a flowchart illustrating the step of obtaining a torque distribution coefficient constraint range according to one embodiment;
FIG. 3 is a flowchart illustrating the step of obtaining a target torque distribution coefficient in one embodiment;
FIG. 4 is a schematic flow chart of an electric vehicle driving torque distribution method in another embodiment;
FIG. 5 is a block diagram showing the construction of a driving torque distribution device for an electric vehicle according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that the terms "first \ second \ third" related to the embodiments of the present invention only distinguish similar objects, and do not represent a specific ordering for the objects, and it should be understood that "first \ second \ third" may exchange a specific order or sequence when allowed. It should be understood that the terms first, second, and third, as used herein, are interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than those illustrated or otherwise described herein.
In an embodiment, a method for distributing driving torque of an electric vehicle is provided, and referring to fig. 1, fig. 1 is a schematic flow chart of the method for distributing driving torque of an electric vehicle in an embodiment, which is described by taking a control terminal of the method applied to an electric vehicle as an example, where the electric vehicle includes a front motor and a rear motor, and the method for distributing driving torque of an electric vehicle may include the following steps:
step S101, acquiring a constraint range of a torque distribution coefficient; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained by the total required torque, the front motor torque and the rear motor torque of the electric vehicle.
The torque can be a basic load form of a transmission shaft of various working machines and is closely related to the factors of the working capacity, energy consumption, efficiency, operation life, safety performance and the like of the power machine; the torque distribution coefficient may be a torque for determining each motor of the electric vehicle, and may be a coefficient of a front motor torque and a rear motor torque, for example. Specifically, the torque distribution coefficient may be:
Figure BDA0002353291910000041
where B may be the torque distribution coefficient, TfFor front motor torque, TrFor rear motor torque, TallIs the total required torque. The control terminal can distribute the total required torque of the electric automobile at the current moment to the front motor and the rear motor respectively according to the preset conditions and the torque distribution coefficients. The torque distribution coefficient may be a torque distribution coefficient within a constraint range, and the control terminal may acquire the constraint range of the torque distribution coefficient, and calculate the torque distribution coefficient within the constraint range.
Step S102, the constraint range of the torque distribution coefficient is divided into a plurality of sub-constraint ranges.
The sub-constraint range may be a plurality of sub-constraint ranges obtained by dividing the torque distribution coefficient, and the control terminal may divide the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges having equal interval lengths, or may divide the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges having unequal interval lengths. Specifically, each interval may be [ C ]N,DN]. Where N may be a natural number and the maximum value of N may be the maximum number of the above-described sub-constraint ranges. The control terminal can respectively carry out optimization search in the sub-constraint ranges to avoidThe result falls into a local optimum.
Step S103, solving the optimized objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimized objective function to be minimum; and the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be comprehensively optimal.
The sub-constraint range may be a sub-constraint range of a torque distribution coefficient, the preset iterative algorithm may be an algorithm for finding an optimal torque distribution coefficient in the sub-constraint range, for example, an improved golden section method, the optimization objective function may be a function for obtaining a torque distribution coefficient that optimizes both stability and economy of the electric vehicle, and the optimization objective function may be obtained by a plurality of sub-objective functions. The control terminal may obtain, in each of the sub-constraint ranges, a target torque distribution coefficient that minimizes an output value of the optimization objective function by a preset iterative algorithm according to the torque distribution coefficient in each of the sub-constraint ranges. The control terminal may select an optimal torque distribution coefficient among the torque distribution coefficients with the minimum order of the optimized objective function output value, that is, the torque distribution coefficient with the minimum order of the optimized objective function output value among the torque distribution coefficients obtained in all the sub-constraint ranges, as the target torque distribution coefficient.
And step S104, obtaining the torque required by the front motor and the torque required by the rear motor of the electric automobile according to the total required torque and the target torque distribution coefficient.
The total required torque may be a total required torque required by the electric vehicle at the present time, and the required torque may be required to be distributed to each motor of the electric vehicle, for example, the total required torque may be distributed to the front motor and the rear motor. After obtaining the target torque distribution coefficient, the control terminal may distribute the total required torque to the front motor and the rear motor according to the formula of the torque distribution coefficient to obtain the torque required by the front motor and the torque required by the rear motor of the electric vehicle.
According to the electric vehicle driving torque distribution method, the torque distribution coefficient constraint range is divided into a plurality of sub-constraint ranges by obtaining the constraint range of the torque distribution coefficient, the optimized objective function is solved in each sub-constraint range according to the torque distribution coefficient and a preset iterative algorithm, the objective torque distribution coefficient enabling the output value of the optimized objective function to be minimum is obtained, the torque distribution coefficient enabling the stability and the economy of an electric vehicle to be optimal is obtained, and the torque required by a front motor and the torque required by a rear motor of the electric vehicle are obtained according to the objective torque distribution coefficient and the total required torque. Compared with the traditional torque distribution method, the method and the device have the advantages that the range of the torque distribution coefficient can be constrained during optimization, the calculated amount is reduced, the extreme torque distribution mode is avoided, the optimal torque distribution coefficient can be calculated in each sub-constraint range, the occurrence of local optimal solution is avoided, the calculation time is shortened, and the effect of optimally distributing the torque with economy and stability is achieved.
In one embodiment, obtaining a constrained range of torque distribution coefficients comprises: acquiring a first constraint range, wherein the first constraint range is obtained according to the external motor characteristics of the electric automobile at the current moment and the total required torque at the current moment; acquiring a second constraint range, wherein the second constraint range is obtained according to a torque distribution coefficient of the electric automobile at the last preset moment, the total required torque at the last preset moment and the speed of the electric automobile at the last preset moment; and obtaining the constraint range of the torque distribution coefficient according to the first constraint range and the second constraint range.
In the present embodiment, the first restriction range and the second restriction range may be used to determine the above-described torque distribution coefficient restriction range. The control terminal can obtain a first constraint range according to the external characteristics of the motor of the electric automobile at the current moment and the total required torque at the current moment, can also obtain a second constraint range according to the torque distribution coefficient of the electric automobile at the last preset moment, the total required torque at the last preset moment and the automobile speed at the last preset moment, and can combine the first constraint range and the second constraint range through preset conditions to obtain the constraint range of the torque distribution coefficient. Specifically, the first restriction range may be a restriction range in which the torque distribution coefficient is calculated based on the characteristic outside the motor, and the second restriction range may be a torque distribution coefficient restriction range based on the torque distribution coefficient at the last preset time. The last preset time may be set according to actual conditions, and may be, for example, a time before a controller calculates a step size. Through the embodiment, the control terminal can determine the constraint range of the torque distribution coefficient according to the external characteristics of the electric automobile and the torque distribution coefficient at the last preset moment, so that the fluctuation of the calculated amount and the torque distribution coefficient is reduced, and the stability of the automobile is improved.
In one embodiment, as shown in FIG. 2, FIG. 2 is a flowchart illustrating the step of obtaining a constrained range of torque distribution coefficients in one embodiment. Acquiring a first constraint range, comprising: acquiring a difference value between the total required torque at the current moment and the external characteristic torque of the rear motor at the current moment; comparing the difference value with 0 to obtain the maximum value; acquiring the sum of the external characteristic torque of the front motor at the current moment and the external characteristic torque of the rear motor at the current moment as the total external characteristic torque of the motor at the current moment; acquiring a first minimum value between the total required torque at the current moment and the total external motor characteristic torque at the current moment; acquiring the ratio of the maximum value to the first minimum value as the minimum value of the first constraint range; acquiring a second minimum value between the external characteristic torque of the front motor at the current moment and the total required torque at the current moment; acquiring the ratio of a second minimum value to the first minimum value as the maximum value of the first constraint range; the first constraint range is determined based on the minimum value of the first constraint range and the maximum value of the first constraint range.
Obtaining a second constraint range comprising: subtracting a first preset value from the actual torque distribution coefficient at the last preset moment to obtain a preselected minimum value; the first preset value is in inverse proportion to the acceleration of the electric automobile; acquiring a maximum value between the preselected minimum value and 0 as a minimum value of a second constraint range; adding a second preset value to the actual torque distribution coefficient at the last preset moment to obtain a preselected maximum value; the second preset value is in inverse proportion to the acceleration of the electric automobile; acquiring a minimum value between the preselected maximum value and 1 as a maximum value of a second constraint range; and determining the second constraint range according to the minimum value of the second constraint range and the maximum value of the second constraint range.
Obtaining a constraint range of the torque distribution coefficient according to the first constraint range and the second constraint range, wherein the constraint range comprises: and acquiring the intersection of the first constraint range and the second constraint range to obtain the constraint range of the torque distribution coefficient.
In this embodiment, the external motor characteristic may be a characteristic of a relationship between a torque T generated on the motor shaft and a corresponding operating speed n. The control terminal may obtain the first constraint range according to the following formula:
Figure BDA0002353291910000051
wherein, Tf maxFor the external characteristic torque of the motor before the present moment, Tr maxThe torque is the external characteristic torque of the motor after the current moment. The control terminal can obtain the total required torque T at the current momentallAnd the external characteristic torque T of the motor after the current momentrmaxAnd the difference between them can be calculated, then the above-mentioned difference can be compared with 0, and the maximum value in the comparison can be taken; the control terminal can also obtain the external characteristic torque of the front motor at the current moment and the torque of the rear motor at the current moment, and can convert the external characteristic torque T of the front motor at the current moment into the external characteristic torque T of the rear motor at the current momentf maxAnd the rear motor torque T at the present timer maxSumming to obtain the total external motor characteristic torque at the current moment, and the control terminal can use the total external motor characteristic torque and the total required torque TallAnd comparing, and taking the minimum value in comparison as the first minimum value. After obtaining the maximum value and the first minimum value in the comparison, the control terminal may obtain a ratio of the maximum value and the first minimum value in the comparison, as the minimum value of the first constraint range. The control terminal can also convert the characteristics of the previous motor at the current moment into the characteristics of the previous motor at the current momentMoment Tf maxAnd the total required torque T at the present timeallComparing and obtaining the minimum value in comparison as the second minimum value, the control terminal may obtain the second minimum value and the first minimum value, that is, the total external motor characteristic torque and the total required torque TallThe ratio of the minimum values in the comparison is used as the maximum value of the first constraint range, and the control terminal can determine the first constraint range through the minimum value of the first constraint range and the maximum value of the first constraint range. Wherein the first constraint range may be a constraint range in which the torque distribution coefficient is calculated based on the characteristic outside the motor. The total required torque TallCan be obtained by a driving component of an electric automobile and the like.
The second constraint range may be obtained by the following equation:
[Bmin2,Bmax2]＝[max(Bt-1+ΔB-,0),min(Bt-1+ΔB+,1)]；
wherein, Bt-1The actual torque distribution coefficient at the last preset time, specifically, the actual torque distribution coefficient at the last preset time can be obtained by the following formula:
Figure BDA0002353291910000061
wherein, Tf_req2Torque, T, required by the motor before the last predetermined momentr_req2The torque required by the motor after the last preset moment. Delta B-Is the maximum value of the torque coefficient of the motor, Delta B+Is the maximum value of the torque coefficient of the motor, Delta B-May be negative, Δ B+May be a positive number. The control terminal may subtract the first preset value from the actual torque distribution coefficient at the last preset time to obtain a preselected minimum value. Wherein the first predetermined value may be Δ B-The first preset value may be inversely proportional to the acceleration of the electric vehicle, that is, the larger the acceleration of the electric vehicle is, the smaller the first preset value is. The control terminal may compare the preselected minimum value with 0 to obtain a maximum value in the comparison as the second valueA minimum value of a constraint range. The control terminal can also add a second preset value to the actual torque distribution coefficient at the last preset moment to obtain a preselected maximum value. Wherein the second predetermined value may be Δ B+The second preset value may be inversely proportional to the acceleration of the electric vehicle, that is, the second preset value may be smaller as the acceleration of the electric vehicle is larger. The control terminal may compare the preselected maximum value with 1 to obtain a maximum value in the comparison as a maximum value of the second constraint range. Wherein, Delta B-And Δ B+May be determined according to a set rule, for example, a theoretical acceleration torque T may be seta＝Tall-ffri(v, α), where v may be the speed of the electric vehicle, α may be the acceleration of the electric vehicle, the theoretical acceleration torque TaThe larger, Δ B-And Δ B+The smaller the absolute value of (a); theoretical acceleration torque TaThe smaller, Δ B-And Δ B+The larger the absolute value of (c). By adopting the method, the influence on the comfort and the safety of the vehicle caused by the large variation range of the torque distribution coefficient can be avoided. Wherein, Delta B-And Δ B+The specific calculation can be performed by a table lookup method, a fuzzy control method, or the like. The control terminal may determine the second constraint range after acquiring the minimum value of the second constraint range and the maximum value of the second constraint range. Wherein the second constraint range may be a torque distribution coefficient constraint range based on a torque distribution coefficient at a last preset time.
The control terminal may also determine the above-described constraint range of the torque distribution coefficient by the following equation:
[Bmin,Bmax]＝[max(Bmin1,Bmin2)，min(Bmax1,Bmax2)]；
the control terminal may obtain an intersection of the first constraint range and the second constraint range after obtaining the first constraint range and the second constraint range, specifically, a minimum value of the torque distribution coefficient constraint range may be a maximum value between a minimum value of the first constraint range and a minimum value of the second constraint range, and a maximum value of the torque distribution coefficient constraint range may be a minimum value between a maximum value of the first constraint range and a maximum value of the second constraint range. Through the embodiment, the control terminal can determine the torque distribution coefficient constraint range through parameters such as the external characteristics of the motor, the total required torque, the actual torque distribution coefficient at the last preset moment and the like, comprehensively considers factors such as the vehicle state, the driving condition and the like, reduces the optimization area, reduces the calculated amount, and can also ensure the stability and the comfort of the vehicle.
In one embodiment, before solving the optimization objective function according to the torque distribution coefficient in each of the sub-constraint ranges and the preset iterative algorithm, the method includes: acquiring a first optimization objective function; the first optimization objective function is a function for calculating an axle load distribution optimal value of the electric automobile; acquiring a second optimization objective function; the second optimization objective function is a function for calculating the optimal value of the total efficiency of the motor of the electric automobile; obtaining an influence parameter of a second optimization objective function; the influence parameter is used for expressing the influence proportion of the second optimization objective function on the optimization objective function; and determining an optimization objective function according to the first optimization objective function, the second optimization objective function and the influence parameters.
In this embodiment, the optimization objective function may be composed of a plurality of optimization objective functions, such as a first optimization objective function and a second optimization objective function. The first optimization objective function can be a stability function based on the axle load proportion distribution of the front axle and the rear axle, the control terminal can obtain the axle load distribution optimal value of the electric automobile through the stability function, the second optimization objective function can be an economic function based on the total efficiency of the motor, and the control terminal can obtain the motor total efficiency optimal value of the electric automobile according to the economic function. In addition, the second objective optimization function also contains an influence parameter, which can be determined from the above-mentioned total required torque, vehicle speed and gradient, which can represent the influence of the above-mentioned second optimization objective function, i.e. the economy function, on the above-mentioned optimization objective function. Specifically, the above-mentioned influence parameter may be represented as w, and the control terminal may comprehensively consider the economy and the vehicle stability for different vehicle driving states, and mayAccording to the total required torque TallThe vehicle acceleration v and the gradient alpha are calculated, the economic optimization target specific gravity w can represent the influence specific gravity of the economic target of the electric vehicle, the larger w is, the smaller w is, and the basic calculation principle of the influence parameter w is as follows: theoretical acceleration torque TaThe larger w, the smaller the theoretical acceleration torque TaThe smaller, the larger w; the larger the gradient α, the smaller w, and the smaller the gradient α, the larger w. The influence parameter w may be calculated by a table lookup method, a fuzzy control method, or the like. The control terminal may determine the optimization objective function according to the first optimization objective function, the second optimization objective function, and the influence parameter. Through this embodiment, control terminal can synthesize and consider motor stability and economic nature, optimizes above-mentioned electric automobile's torque distribution coefficient, has realized the effect that improves electric automobile motor's stability and economic nature.
In one embodiment, obtaining a first optimization objective function comprises: obtaining a first optimization objective function according to the front axle longitudinal force, the rear axle longitudinal force, the front axle load and the rear axle load of the electric automobile; obtaining a second optimization objective function, comprising: determining a first efficiency function according to the front motor efficiency, the front motor torque and the front motor rotating speed of the electric automobile; determining a second efficiency function according to the rear motor efficiency, the rear motor torque and the rear motor rotating speed of the electric automobile; and obtaining a second optimization objective function according to the first efficiency function, the second efficiency function and the total required torque.
In this embodiment, the axle load may be a load borne by the axle. The control terminal may obtain the first optimization objective function through the following formula:
Figure BDA0002353291910000071
wherein the electric vehicle may comprise a front drive axle and a rear drive axle, the above-mentioned optimization objective function may be used in a straight line situation, and thus
Figure BDA0002353291910000072
Fx1For front axle longitudinal forces, Fx2Is the rear axle longitudinal force. Specifically, Fx1And Fx2Can be approximately calculated as:
Figure BDA0002353291910000073
wherein, TfFor front motor torque, TrIs the rear motor torque, ifIs the total reduction ratio of the front drive axle, irFor total rear axle reduction ratio, RwIs the radius of the tire, IwMay be the moment of inertia of the drive axle equivalent to the output shaft of the motor,
Figure BDA0002353291910000074
it may be the angular acceleration of the front motor,
Figure BDA0002353291910000075
may be the rear motor angular acceleration. In addition, the first optimization objective function may include front axle load Fz1And rear axle load Fz2The axle load can be an axle load estimation part based on a reference model, and the control terminal can estimate the axle load F of the front axle according to the acceleration a and the gradient signal alpha of the electric automobilez1Axle load F of rear axlez2The front axle load Fz1Axle load F of rear axlez2May be used as input to the calculation of the optimization objective function described above. The control terminal may be according to the above
Figure BDA0002353291910000076
The above first optimization objective function is obtained from the mean square error and the expectation.
On the other hand, the control terminal may obtain the second optimization objective function according to the following formula:
Figure BDA0002353291910000077
wherein eta isf(Tf,nf) Characterizing front Motor efficiency and front Motor Torque TfFront motor speed nfFunction of between, ηr(Tr,nr) Characterizing rear Motor efficiency and rear Motor Torque TrRear motor speed nrA function of (d). Eta abovef(Tf,nf) And ηr(Tr,nr) It can be calculated by means of a look-up table. The control terminal can obtain the torque T of the front motorfAnd front motor efficiency ηf(Tf,nf) Can also obtain the rear motor torque TrAnd rear motor efficiency ηr(Tr,nr) And the above two ratios can be summed, and the total required torque T can be obtainedallAnd subtracting 1 from the ratio obtained by summing the ratios to obtain the second optimization objective function. Front motor torque T in the first and second optimization functionsfTorque T of rear motorrCalculated by the following formula: t isf＝BTall，
Figure BDA0002353291910000081
The control terminal may determine the optimization objective function according to the first optimization objective function, the second optimization objective function, and the economic optimization objective proportion w, and specifically, may be as follows: f (B) ═ fγ(B)+wfη(B)。
In one embodiment, as shown in FIG. 3, FIG. 3 is a flow chart illustrating the step of obtaining the target torque distribution coefficient in one embodiment. Solving the optimization objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimization objective function to be minimum, wherein the method comprises the following steps: taking a first torque distribution coefficient which is separated from the minimum value in the sub-constraint range by a first preset value as a first input value of the optimization objective function; taking a second torque distribution coefficient which is separated from the minimum value in the sub-constraint range by a second preset value as a second input value of the optimization objective function; respectively inputting the first input value and the second input value into an optimization objective function to obtain a corresponding first output value and a corresponding second output value; adjusting the sub-constraint range according to the first output value and the second output value, so that the sub-constraint range is adjusted to the input value corresponding to the smaller output value of the first output value and the second output value; returning to the step of executing a first torque distribution coefficient which is separated from the minimum value in the sub-constraint range by a first preset value as a first input value of the optimization objective function, and stopping adjusting the sub-constraint range until a preset condition is reached; the preset condition is determined according to the sizes of the first output value and the second output value, the output value of the second optimization objective function, the output value of the first optimization objective function or the iteration times; taking the average value of the first input value and the second input value as the optimal torque distribution coefficient corresponding to the sub-constraint range; and selecting the optimal torque distribution coefficient which enables the output value of the optimization objective function to be minimum from the optimal torque distribution coefficients corresponding to the multiple sub-constraint ranges as the target torque distribution coefficient.
In this embodiment, the control terminal may obtain, in each of the sub-constraint ranges, a torque distribution coefficient in which an output value of the optimization objective function is minimized. Wherein, the optimization objective function may include a golden section method, as shown in fig. 3, the control terminal may constrain each sub-constraint range [ C ]N,DN]Defining the value of initialized C and the value of D as the range of the optimization objective function, and initializing k to be 0; in this range, two test points are taken as input, which may be r1 and r2, for example, r1 and r2 may be specifically expressed as in the formula of FIG. 3, wherein 0.382(D-C) may be a first preset value, 0.618(D-C) may be a second preset value, the control terminal may take as a first input value of the optimization objective function a first torque distribution coefficient from a minimum value in the sub-constraint range by the first preset value, take as a second input value of the optimization objective function a second torque distribution coefficient from a minimum value in the sub-constraint range by the second preset value, and the optimization objective function can be respectively input according to the first input value and the second input value to obtain a corresponding first output value and a corresponding second output value, and the sub-constraint range can be adjusted according to the first output value and the second output value to enable the sub-constraint range to be output to the first output.And adjusting the input value corresponding to the smaller output value of the value and the second output value. Specifically, the control terminal may input the r1 and r2 into the optimization objective function, determine the magnitude of the output value, adjust the maximum value of the range to the value represented by r2 when the output value of r2 is large, adjust the second input value r2 to the value represented by the first input value r1, and then solve the first input value r1 according to the adjusted range by the trial formula shown in fig. 3, so that the range is adjusted and reduced to the region where the small r1 is located; when the output value of r2 is smaller, the minimum value of the above range may be adjusted to the value represented by r1, the first input value r1 may be adjusted to the value represented by the second input value r2, and then the second input value r2 may be solved according to the adjusted range by the trial formula in fig. 3, so that the range is adjusted and reduced to the smaller region where r2 is located.
The control terminal may, after adjusting the values of r1 and r2, return to performing the step of taking as a first input value of the optimization objective function a first torque distribution coefficient that is a first preset value away from the minimum value in the sub-constraint range, and stop adjusting the sub-constraint range until a preset condition is reached. In one embodiment, the preset condition includes at least one of: the interval length of the adjusted sub-constraint range is smaller than a first threshold; the output value of the first optimization objective function is smaller than a second threshold value; the output value of the second optimization objective function is smaller than a third threshold value; the number of iterations reaches a fourth threshold. Specifically, the preset conditions may include: min (f) when the section length r2-r1 of the current remaining range is smaller than the set threshold epsilon 1η(r1),fη(r2))<ε 2, i.e., the economic optimization goal at one of points r1 or r2, may be less than the set thresholds ε 2, Min (f)γ(r1),fγ(r2))<Epsilon 3, namely, the mean square deviation value of the tire conformity rate is smaller than a set threshold epsilon 3, and the iteration number k is larger than a set threshold kmAt least one of (1). When the adjustment of the above-mentioned range is stopped, the control terminal may take the average value of the first input value r1 and the second input value r2 for stopping the adjustment as the optimal torque distribution coefficient of the sub-restriction range, and the control terminal may obtain the optimal rotation in the plurality of sub-restriction rangesMoment distribution coefficient BN(N-1, 2 … p), where p may be the number of sub-constraints, and the control terminal may filter the optimal objective function f (B) from a plurality of optimal torque distribution coefficientsN) Minimum BNDistributing coefficient B for target torqueOPT. Through the embodiment, the control terminal can optimize the torque of the electric automobile on line based on the optimization objective function of the search principle, comprehensively considers the economic and stability factors, and can obtain the target torque distribution coefficient according to a plurality of stop conditions, thereby reducing the calculated amount of the torque on-line optimization and improving the real-time performance of the torque on-line optimization.
In one embodiment, obtaining the torque required by the front motor and the torque required by the rear motor of the electric vehicle according to the total required torque and the target torque distribution coefficient comprises: calculating a function and a target torque distribution coefficient according to the motor driving torque to obtain the expected torque of a front motor and the expected torque of a rear motor of the electric automobile; the motor driving torque calculation function is obtained according to the torque distribution coefficient and the total required torque; when the current motor expected torque and the rear motor expected torque are both within a preset range of an electronic stability system of the vehicle body, determining that the front motor expected torque and the rear motor expected torque are respectively the torque required by the front motor and the torque required by the rear motor; when the expected torque of the front motor or the expected torque of the rear motor is out of the preset range of the electronic stability system of the automobile body, the expected torque of the front motor or the expected torque of the rear motor is adjusted to be within the preset range, and the torque required by the front motor and the torque required by the rear motor are obtained according to the adjusted expected torque of the front motor and the adjusted expected torque of the rear motor.
In this embodiment, the control terminal may obtain the desired torque of the front motor and the desired torque of the rear motor of the electric vehicle according to the motor driving torque calculation function and the target torque distribution coefficient. Specifically, the motor drive torque calculation function may be as follows: t isf_req＝BTall；Tr_req＝Tall-Tf_req(ii) a Wherein, Tf_req1Desired torque demand, T, for the front motorr_req1The required torque is expected for the rear motor. The electronic stability control system of the vehicle body can dry the driving torqueIn advance, the vehicle body electronic stability control system can output a torque intervention signal, the control terminal can determine a front motor torque preset range and a rear motor torque preset range according to the torque intervention signal output by the vehicle body electronic stability control system, the front motor expected torque and the rear motor expected torque are limited in the preset ranges, and when the front motor expected torque or the rear motor expected torque exceeds the preset ranges, the motor torque exceeding the ranges can be adjusted to the preset ranges to obtain the final torque required by the motor. The preset range may be a range obtained according to the torque intervention signal, specifically, when the desired torque of the front motor or the desired torque of the rear motor is too large or too small, the stability of the vehicle may be affected, and at this time, the control terminal may obtain, as the preset range, a range of torque enabling the vehicle to stably run according to the torque intervention signal. The torque required by the motor includes the torque T required by the front motorf_req2And torque T required by the rear motorr_req2. The control terminal can distribute the torque required by the front motor and the torque required by the rear motor after completing the distribution of the torque required by the front motor and the torque required by the rear motorf_req2And Tr_req2The torque required by the front motor and the torque required by the rear motor at the last preset time may be used to calculate the above-described torque distribution coefficient restriction range. Through the embodiment, the control terminal can distribute the total required torque to the front motor and the rear motor of the electric automobile through the target torque distribution coefficient, and can limit the torque through the automobile body electronic stability system, so that the stability and the economy of the torque distribution of the electric automobile are improved.
In one embodiment, as shown in fig. 4, fig. 4 is a schematic flow chart of a driving torque distribution method of an electric vehicle in another embodiment. The control terminal can calculate a torque distribution coefficient constraint range according to the torque distribution coefficient constraint calculated based on the external characteristics of the motor and the torque distribution coefficient constraint calculated based on the torque distribution coefficient at the last moment, optimally divide the constraint range into sections, calculate a target torque distribution coefficient according to the divided sub-constraint range based on an improved golden section method, calculate expected torque of a front motor and expected torque of a rear motor of the electric automobile through the motor driving torque function, and limit the expected torque through an electronic stability control system of the automobile body to obtain the torque required by the front motor and the torque required by the rear motor. The calculation of the optimized objective function based on the improved golden section method can further comprise the steps of estimating the axle load based on a reference model and calculating an optimized objective influence parameter. Through the embodiment, the control terminal searches the target torque distribution coefficient from the plurality of divided sub-constraint ranges, integrates various factors, obtains the torque required by the front motor and the torque required by the rear motor of the electric automobile, and achieves the effect of improving the stability and the economy of the torque optimization of the electric automobile.
In an embodiment, an electric vehicle driving torque distribution device is provided, and referring to fig. 5, fig. 5 is a block diagram illustrating a structure of the electric vehicle driving torque distribution device in an embodiment, and the electric vehicle driving torque distribution device may include:
an obtaining module 500 for obtaining a constraint range of a torque distribution coefficient; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained through the total required torque, the front motor torque and the rear motor torque of the electric automobile;
a dividing module 502 for dividing the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges;
a calculating module 504, configured to solve an optimized objective function according to the torque distribution coefficient in each of the sub-constraint ranges and a preset iterative algorithm, so as to obtain a target torque distribution coefficient that minimizes an output value of the optimized objective function; the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be optimal;
and the distribution module 506 is configured to obtain a torque required by a front motor and a torque required by a rear motor of the electric vehicle according to the total required torque and the target torque distribution coefficient.
The electric vehicle driving torque distribution device of the present invention corresponds to the electric vehicle driving torque distribution method of the present invention one to one, and for the specific limitations of the electric vehicle driving torque distribution device, reference may be made to the limitations of the electric vehicle driving torque distribution method in the foregoing description, and the technical features and the advantages thereof described in the embodiments of the electric vehicle driving torque distribution method are all applicable to the embodiments of the electric vehicle driving torque distribution device, and are not described herein again. The modules in the electric vehicle driving torque distribution device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be an on-board processing chip, and the internal structure diagram of the computer device may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device can be used for storing data such as the driving torque of the electric automobile. The communication interface of the computer device is used for connecting and communicating with the control devices of the various components of the vehicle. The computer program is executed by a processor to implement an electric vehicle drive torque distribution method.
Those skilled in the art will appreciate that the configuration shown in fig. 6 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing devices to which aspects of the present invention may be applied, and that a particular computing device may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, which includes a processor and a memory, the memory storing a computer program, the processor implementing the electric vehicle driving torque distribution method according to any one of the above embodiments when executing the computer program.
It will be understood by those skilled in the art that all or part of the processes of implementing the method for allocating driving torque of an electric vehicle according to any one of the above embodiments may be implemented by a computer program, which may be stored in a non-volatile computer readable storage medium, and when executed, may include the processes of the above embodiments of the method. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration, and not limitation, RAM is available in a variety of forms.
Accordingly, in an embodiment, a computer readable storage medium is also provided, on which a computer program is stored, wherein the program is executed by a processor to implement the electric vehicle driving torque distribution method according to any one of the above embodiments.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A method of distributing drive torque for an electric vehicle, the electric vehicle including a front motor and a rear motor, the method comprising the steps of:
acquiring a constraint range of a torque distribution coefficient; the method comprises the following steps: acquiring a first constraint range, wherein the first constraint range is obtained according to the external motor characteristics of the electric automobile at the current moment and the total required torque at the current moment; the motor external characteristics are characteristics of a relation between a torque generated on a motor shaft of the electric vehicle and a corresponding operation rotating speed; acquiring a second constraint range, wherein the second constraint range is obtained according to a torque distribution coefficient of the electric automobile at the last preset moment, a total required torque at the last preset moment and a vehicle speed at the last preset moment; obtaining a constraint range of the torque distribution coefficient according to the intersection of the first constraint range and the second constraint range; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained through the total required torque, the front motor torque and the rear motor torque of the electric automobile;
dividing the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges;
solving an optimization objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimization objective function to be minimum; the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be optimal; the optimization objective function comprises a first optimization objective function obtained based on the axle load distribution of the electric automobile and a second optimization objective function obtained based on an influence parameter and the total motor efficiency of the electric automobile; the influence parameter characterizes influence proportion of the second optimization objective function on the optimization objective function;
and obtaining the torque required by the front motor and the torque required by the rear motor of the electric automobile according to the total required torque and the target torque distribution coefficient.
2. The method of claim 1, wherein obtaining the first constrained range comprises:
acquiring a difference value between the total required torque at the current moment and the external characteristic torque of the rear motor at the current moment;
comparing the difference value with 0 to obtain the maximum value;
acquiring the sum of the external characteristic torque of the front motor at the current moment and the external characteristic torque of the rear motor at the current moment as the total external characteristic torque of the motor at the current moment;
acquiring a first minimum value between the total required torque at the current moment and the total external motor characteristic torque at the current moment;
acquiring the ratio of the maximum value to the first minimum value as the minimum value of the first constraint range;
acquiring a second minimum value between the external characteristic torque of the front motor at the current moment and the total required torque at the current moment;
acquiring the ratio of the second minimum value to the first minimum value as the maximum value of the first constraint range;
determining the first constraint range according to the minimum value of the first constraint range and the maximum value of the first constraint range;
the obtaining of the second constraint range includes:
subtracting a first preset value from the actual torque distribution coefficient at the last preset moment to obtain a preselected minimum value; the first preset value is inversely proportional to the acceleration of the electric vehicle;
acquiring the maximum value between the preselected minimum value and 0 as the minimum value of the second constraint range;
subtracting a second preset value from the actual torque distribution coefficient at the last preset moment to obtain a preselected maximum value; the second preset value is inversely proportional to the acceleration of the electric vehicle;
acquiring a minimum value between the preselected maximum value and 1 as a maximum value of the second constraint range;
determining the second constraint range according to the minimum value of the second constraint range and the maximum value of the second constraint range;
the obtaining of the constraint range of the torque distribution coefficient according to the first constraint range and the second constraint range includes:
and acquiring the intersection of the first constraint range and the second constraint range to obtain the constraint range of the torque distribution coefficient.
3. The method according to claim 1, wherein before solving the optimization objective function according to the torque distribution coefficients in each of the sub-constraint ranges and the preset iterative algorithm, the method comprises:
acquiring a first optimization objective function; the first optimization objective function is a function for calculating an axle load distribution optimal value of the electric automobile;
acquiring a second optimization objective function; the second optimization objective function is a function for calculating the optimal value of the total motor efficiency of the electric automobile;
obtaining an influence parameter of the second optimization objective function; the influence parameter is used for expressing the influence proportion of the second optimization objective function on the optimization objective function;
and determining the optimization objective function according to the first optimization objective function, the second optimization objective function and the influence parameters.
4. The method of claim 3, wherein obtaining the first optimization objective function comprises:
and obtaining the first optimization objective function according to the front axle longitudinal force, the rear axle longitudinal force, the front axle load and the rear axle load of the electric automobile.
5. The method of claim 3, wherein obtaining a second optimization objective function comprises:
determining a first efficiency function according to the front motor efficiency, the front motor torque and the front motor rotating speed of the electric automobile;
determining a second efficiency function according to the rear motor efficiency, the rear motor torque and the rear motor rotating speed of the electric automobile;
and obtaining the second optimization objective function according to the first efficiency function, the second efficiency function and the total required torque.
6. The method according to claim 3, wherein the solving an optimization objective function according to the torque distribution coefficient in each of the sub-constraint ranges and a preset iterative algorithm to obtain a target torque distribution coefficient that minimizes an output value of the optimization objective function comprises:
taking a first torque distribution coefficient which is a first preset value away from a minimum value in the sub-constraint range as a first input value of the optimization objective function;
taking a second torque distribution coefficient which is a second preset value away from the minimum value in the sub-constraint range as a second input value of the optimization objective function;
inputting the first input value and the second input value into the optimization objective function respectively to obtain a corresponding first output value and a corresponding second output value;
according to the first output value and the second output value, adjusting the sub-constraint range to enable the sub-constraint range to be adjusted to an input value corresponding to the smaller output value of the first output value and the second output value;
returning to performing the step of taking a first torque distribution coefficient which is a first preset value away from a minimum value in the sub-constraint range as a first input value of the optimization objective function, and stopping adjusting the sub-constraint range until a preset condition is reached; the preset conditions comprise at least one of the interval length of the adjusted sub-constraint range being smaller than a first threshold, the output value of the first optimization objective function being smaller than a second threshold, the output value of the second optimization objective function being smaller than a third threshold, and the number of iterations reaching a fourth threshold;
taking the average value of the first input value and the second input value as the optimal torque distribution coefficient corresponding to the sub-constraint range;
and selecting the optimal torque distribution coefficient which enables the output value of the optimization objective function to be minimum from the optimal torque distribution coefficients corresponding to the sub-constraint ranges as a target torque distribution coefficient.
7. The method according to claim 1, wherein the obtaining the torque required by the front motor and the torque required by the rear motor of the electric vehicle according to the total required torque and the target torque distribution coefficient comprises:
obtaining a front motor expected torque and a rear motor expected torque of the electric automobile according to a motor driving torque calculation function and the target torque distribution coefficient; the motor driving torque calculation function is obtained according to the torque distribution coefficient and the total required torque;
when the expected torque of the front motor and the expected torque of the rear motor are both within a preset range of an electronic stability system of a vehicle body, determining that the expected torque of the front motor and the expected torque of the rear motor are respectively the torque required by the front motor and the torque required by the rear motor;
when the expected torque of the front motor or the expected torque of the rear motor is out of a preset range of an electronic stability system of a vehicle body, the expected torque of the front motor or the expected torque of the rear motor is adjusted to be within the preset range, and the torque required by the front motor and the torque required by the rear motor are obtained according to the adjusted expected torque of the front motor and the adjusted expected torque of the rear motor.
8. An electric vehicle drive torque distribution apparatus, the electric vehicle including a front motor and a rear motor, the apparatus comprising:
the acquisition module is used for acquiring a constraint range of the torque distribution coefficient; the method is specifically used for: acquiring a first constraint range, wherein the first constraint range is obtained according to the external motor characteristics of the electric automobile at the current moment and the total required torque at the current moment; the motor external characteristics are characteristics of a relation between a torque generated on a motor shaft of the electric vehicle and a corresponding operation rotating speed; acquiring a second constraint range, wherein the second constraint range is obtained according to a torque distribution coefficient of the electric automobile at the last preset moment, a total required torque at the last preset moment and a vehicle speed at the last preset moment; obtaining a constraint range of the torque distribution coefficient according to the intersection of the first constraint range and the second constraint range; the torque distribution coefficient is used for determining the torque of each motor in the electric automobile; the torque distribution coefficient is obtained through the total required torque, the front motor torque and the rear motor torque of the electric automobile;
the dividing module is used for dividing the constraint range of the torque distribution coefficient into a plurality of sub-constraint ranges;
the calculation module is used for solving an optimized objective function according to the torque distribution coefficient in each sub-constraint range and a preset iterative algorithm to obtain a target torque distribution coefficient which enables the output value of the optimized objective function to be minimum; the optimization objective function is used for obtaining a torque distribution coefficient which enables the stability and the economy of the electric automobile to be optimal; the optimization objective function comprises a first optimization objective function obtained based on the axle load distribution of the electric automobile and a second optimization objective function obtained based on an influence parameter and the total motor efficiency of the electric automobile; the influence parameter characterizes influence proportion of the second optimization objective function on the optimization objective function;
and the distribution module is used for obtaining the torque required by the front motor and the torque required by the rear motor of the electric automobile according to the total required torque and the target torque distribution coefficient.
9. A computer device comprising a processor and a memory, the memory storing a computer program, wherein the processor when executing the computer program implements the steps of the electric vehicle drive torque distribution method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the electric vehicle drive torque distribution method according to any one of claims 1 to 7.
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