CN108215747A - The bi-motor arrangement of pure electric automobile and the torque optimization method based on convex optimized algorithm - Google Patents

The bi-motor arrangement of pure electric automobile and the torque optimization method based on convex optimized algorithm Download PDF

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CN108215747A
CN108215747A CN201810002393.8A CN201810002393A CN108215747A CN 108215747 A CN108215747 A CN 108215747A CN 201810002393 A CN201810002393 A CN 201810002393A CN 108215747 A CN108215747 A CN 108215747A
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max
dem
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automobile
battery
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CN108215747B (en
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胡晓松
李亚鹏
冯飞
谢翌
唐小林
杨亚联
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Chongqing University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K1/00—Arrangement or mounting of electrical propulsion units
    • B60K1/02—Arrangement or mounting of electrical propulsion units comprising more than one electric motor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD

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Abstract

It is comprised the following steps the present invention relates to a kind of bi-motor arrangement of pure electric automobile with the torque optimization method based on convex optimized algorithm, this method：S1：According to the parameter of automobile, the Longitudinal Dynamic Model of automobile is established；S2：The state of cyclic operation of automobile is selected, according to selected state of cyclic operation, calculates the demand torque T of automobiledem(k), demand power Pdem(k), greatest requirements torque Tdem,maxWith maximum demanded power Pdem,max；S3：Under the premise of assuming that the capacity of automobile batteries meets dynamic property demand, according to Tdem,maxAnd Pdem,maxValue, select the motor size and battery size of automobile；S4：Convex optimization processing is carried out to the motor and battery of automobile by convex optimized algorithm；S5：Each component working state of car transmissions is constrained；S6：Determine cost objective function.The method of the present invention selection bi-motor arrangement compensates for the single motor arrangement ineffective shortcoming of motor in electric automobile, while the optimization algorithm calculating time of the present invention is fast, as a result accurately.

Description

Double-motor arrangement of pure electric vehicle and torque optimization method based on convex optimization algorithm
Technical Field
The invention belongs to the technical field of new energy automobiles, and relates to a double-motor arrangement of a pure electric automobile and a torque optimization method based on a convex optimization algorithm.
Background
With the increasing shortage of global petroleum resources and the increasing severity of environmental pollution caused by exhaust emission of traditional automobiles, all countries are forced to support the development of pure electric vehicles. Compared with the traditional automobile or the hybrid electric automobile, the pure electric automobile has the outstanding advantages of zero emission and no pollution.
The transmission system of a pure electric vehicle usually consists of a power battery, a driving motor and a gearbox, and with the maturity of motor control technology, the existing electric vehicle adopts a structure without a transmission to directly control the rotating speed of the motor to realize the change of the vehicle speed. In the prior art, one power battery and one driving motor are adopted, or one power battery and two same driving motors are adopted. And the four-motor-driven electric vehicle is rarely applied to a practical vehicle due to the complicated electromechanical coupling control. The efficiency of the motor of the existing pure electric vehicle can reach 95% or even higher to the maximum, for the pure electric vehicle with a single motor, the required torque Tdem is directly provided by one motor, in order to meet the dynamic requirement, a motor with larger size is generally selected, and the maximum output torque and the maximum output power are larger. Although such a power train arrangement is simple, the electric motor mostly operates in a low efficiency region, and much electric power is wasted on the battery. In order to solve the problem that the motors work in a low-efficiency area, researchers develop that two motors with smaller relative sizes and the same performance are adopted to averagely distribute required torque, the two motors work in a high-efficiency area at the same time, and then the efficiency of a transmission system is improved. The above two arrangement structures both can make the electric quantity of the battery not fully utilized, however, in order to ensure the dynamic property of the whole vehicle, the size of the battery must be increased, which leads to higher cost of the pure electric vehicle and hinders the development of the electric vehicle.
In the existing optimization algorithm, a Dynamic Programming (DP) algorithm can ensure that the optimal solution is globally optimal, but the DP calculation time increases exponentially with the increase of control variables, so that the calculation load is large. The electric vehicle with the dual-motor structure adopts a torque average distribution strategy, and the control strategy is simple and can save time, but cannot ensure that the distribution of the torque is globally optimal.
Disclosure of Invention
In view of this, the present invention provides a dual-motor arrangement for a pure electric vehicle and a torque optimization method based on a convex optimization algorithm, so as to achieve the purposes of obtaining an optimal solution as a global optimal solution within an allowable error, and obtaining accurate results with less calculation time.
In order to achieve the purpose, the invention provides the following technical scheme:
the method for arranging double motors of the pure electric vehicle and optimizing the torque based on the convex optimization algorithm comprises the following steps of:
s1: establishing a longitudinal dynamic model of the automobile according to the parameters of the automobile;
s2: selecting the circulation working condition of the automobile, and calculating the required torque T of the automobile according to the selected circulation working conditiondem(k) Required power Pdem(k) Maximum required torque Tdem,maxAnd maximum power demand Pdem,max；
S3: according to T, on the premise that the capacity of the automobile battery meets the dynamic demanddem,maxAnd Pdem,maxSelecting the motor size and the battery size of the automobile;
s4: carrying out convex optimization processing on a motor and a battery of the automobile through a convex optimization algorithm;
s5: the working states of all parts of the automobile transmission system are restrained;
s6: a cost objective function is determined.
Further, in step S1, the longitudinal dynamics model of the automobile is established as follows:
wherein, Ft(k) Which represents the traction of the vehicle,representing the air resistance of the vehicle during travel, cdIs the coefficient of air resistance, AfIs the windward area of the automobile, rho is the air density, v is the running speed of the automobile, k represents the running time of the automobile, g is the gravity acceleration, crThe rolling resistance coefficient of the road, β the road gradient, a the acceleration of the vehicle during driving, mtotRepresenting the mass of the car.
Further, in step S2, the required torque T of the automobile is calculateddem(k) Required power Pdem(k) Maximum required torque Tdem,maxAnd maximum power demand Pdem,maxComprises the following steps:
Pdem(k)＝Ft(k)*v(k)
Tdem(k)＝Ft(k)*rwheel
Tdem,max＝max(Tdem(k))
Pdem,max＝max(Pdem(k))
wherein, Ft(k) Is the traction of the vehicle at time k, v (k) is the speed of the vehicle at time k, rwheelIs the wheel radius of the automobile.
Further, the motor size and the battery size of the automobile are selected in step S3 to satisfy:
TEM2,max>TEM1,max
PEM2,max>PEM1,max
TEM1,max+TEM2,max≥Tdem,max
Pbat,max≥Pdem,max
wherein, TEM2,maxIs the maximum output torque, T, of the rear wheel motor of the vehicleEM1,maxIs the maximum output torque, P, of the motor of the front wheel of the automobileEM2,maxIs the maximum output power, P, of the rear wheel motor of the vehicleEM1,maxFor the maximum output power, P, of the motor of the front wheel of the vehiclebat,maxThe maximum output power of the battery.
Further, in step S4, the convex optimization processing is:
VOC(k)＝b0*SOC(k)+b1
wherein, PEMi,loss(k) The loss power of the motor at time k, aij(i 1,2, j 1,2,3) is a coefficient of power loss, VOCIs the open circuit voltage of the battery, TEMi(k) (i is 1,2) is the output torque of the front and rear wheel motors at time k, b0,b1To fit the coefficients of the battery voltage, which are constant values, SOC (k) is the state of charge of the automotive battery at time k.
Further, the step S5 is to constrain the operating states of the components of the vehicle transmission system, specifically:
TEMi(k)∈[TENi,min,TEMi.max]
Pbat(k)∈[Pbat,min,Pbat.max]*sbat
Ebat∈[SOCmin,SOCmax]*Voc*Q*sbat
sbat∈[sbat,min,sbat,max]
wherein T isEMi(k) For the output torque of the front and rear wheel motors of the vehicle at time k, Pbat(k) Is the power of the battery at time k, EbatFor storing the charge of the battery, Pbat,min,Pbat.maxMinimum and maximum values of battery power, SOCmin,SOCmaxMinimum and maximum values of the battery state of charge, V, respectivelyocIs the open circuit voltage of the battery, Q is the capacity of the battery, sbatIs the size factor, s, of the batterybat,min,sbat,maxRespectively, the minimum and maximum values of the battery size factor.
Further, the cost objective function in step S6 is:
Jcost＝min costbat+∫Pbatdt
costbat＝wb*sbat
wherein, costbatTo the cost of the battery, wbIs the cost factor of the battery.
The invention has the beneficial effects that:
1. double-motor arrangement is selected, and the defect that the working efficiency of the motor of the electric automobile arranged by a single motor is low is overcome.
2. When selecting the size of the motor, two motors with different sizes are selected, and compared with an arrangement scheme of two same motors, the time for the two motors to work in a low-efficiency area at the same time is reduced.
3. The torque adopts an optimal distribution algorithm, so that the two motors can work in a high-efficiency area at the same time, and the energy utilization efficiency is improved.
4. The size of the power battery can be matched with that of the motor, and the cost of the whole vehicle is saved.
5. The convex optimization algorithm has the advantages of fast calculation time and accurate result.
Drawings
In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a diagram of a vehicle transmission system of the method of the present invention;
FIG. 2 is a graph of the efficiency of selected small motors of the method of the present invention;
FIG. 3 is a graph of the efficiency of a selected large motor of the method of the present invention;
fig. 4 shows the power flow and the torque flow of the motor vehicle according to the invention during driving.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
The implementation of the invention can be realized by a pure electric bus model, as shown in figure 1, the electric bus model is provided with two driving motors which are respectively arranged on a front axle and a rear axle, the rear axle adopts a motor 2 with larger size, the maximum output torque and the output power of the motor 2 are both larger than those of a motor 1 of the front axle, the efficiency graphs of the two motors are shown in figures 2 and 3, the high efficiency areas of the two motors are different due to different initial sizes, wherein the high efficiency area of the motor 1 is in low torque (400N)m-800N m), high speed region, while the electric machine 2 is in high torque (600N m-1000N m), medium speed region. The dynamic property of the vehicle can be satisfied due to the drive of the two motors, and in addition, the required torque T is converted into the required torque T by using an optimal control algorithm due to the different efficiency maps of the two motorsdemThe torque distribution principle is specified in fig. 4 for both motors.
The method comprises the following specific steps:
s1: firstly, a passenger car dynamic model is established according to car parameters, and at the moment k, the traction force of a car is as follows:
wherein,is the air resistance of the automobile during running, mtotgcrcos (β (k)) is rolling resistance, mtotgsin (β (k)) is the climbing resistance, mtota (k) is acceleration resistance. Ft(k) Indicating the traction of the vehicle, cdIs the coefficient of air resistance, AfIs the windward area of the automobile, rho is the air density, v is the running speed of the automobile, k represents the running time of the automobile, g is the gravity acceleration, crThe rolling resistance coefficient of the road, β the road gradient, a the acceleration of the vehicle during driving, mtotRepresenting the mass of the car.
S2: randomly selecting a cyclic working condition, and calculating the required torque T of the automobile according to the selected cyclic working conditiondem(k) Required power Pdem(k) Maximum required torque Tdem,maxAnd maximum power demand Pdem,max；
Pdem(k)＝Ft(k)*v(k)
Tdem(k)＝Ft(k)*rwheel
Tdem,max＝max(Tdem(k))
Pdem,max＝max(Pdem(k))
Wherein, Ft(k) Is the traction of the vehicle at time k, v (k) is the speed of the vehicle at time k, rwheelIs the wheel radius of the automobile.
S3: assuming that the capacity of the battery meets the dynamic demand, according to Tdem,maxAnd Pdem,maxAnd selecting a suitable motor and battery size to satisfy:
TEM2,max>TEM1,max
PEM2,max>PEM1,max
TEM1,max+TEM2,max≥Tdem,max
Pbat,max≥Pdem,max
wherein, TEM2,maxIs the maximum output torque, T, of the motor (motor 2) of the rear wheel of the automobileEM1,maxIs the maximum output torque, P, of the motor (motor 1) of the front wheel of the automobileEM2,maxIs the maximum output power, P, of the motor 2 of the vehicleEM1,maxIs the maximum output power, P, of the motor 1 of the vehiclebat,maxThe maximum output power of the battery.
In addition, in the cycle, the same rotation speeds of the motor 1 and the motor 2 are always satisfied and maintained:
ωEM1＝ωEM2
s4: the invention carries out convex optimization processing on a motor and a battery of an automobile by a convex optimization algorithm, the invention expresses the power loss of the motor by a quadratic fitting mode, in addition, the voltage and the charge state of the battery can be expressed by a linear relational expression, and the convex processing steps are as follows:
VOC(k)＝b0*SOC(k)+b1
wherein, PEMi,loss(k) The loss power of the motor at time k, aij(i 1,2, j 1,2,3) is a coefficient of power loss, VOCIs the open circuit voltage of the battery, TEMi(k) (i is 1,2) is the output torque of the front and rear wheel motors at time k, b0,b1To fit the coefficients of the battery voltage, which are constant values, SOC (k) is the state of charge of the automotive battery at time k.
S5: the working states of all parts of a passenger car transmission system are restrained:
TEMi(k)∈[TENi,min,TEMi.max]
Pbat(k)∈[Pbat,min,Pbat.max]*sbat
Ebat∈[SOCmin,SOCmax]*Voc*Q*sbat
sbat∈[sbat,min,sbat,max]
TENi,min,TEMi.maxrespectively representing the minimum and maximum output torques, P, of the front and rear wheel motorsbat(k) Is the power of the battery at time k, EbatFor storing the charge of the battery, Pbat,min,Pbat.maxMinimum and maximum values of battery power, SOCmin,SOCmaxMinimum and maximum values of the battery state of charge, V, respectivelyocIs the open circuit voltage of the battery, Q is the capacity of the battery, sbatIs the size factor, s, of the batterybat,min,sbat,maxRespectively, the minimum and maximum values of the battery size factor.
S6: determining a cost objective function JcostThe objective function determined by the method of the invention not only is the energy consumption in the cycle working condition, but also includes the cost of the battery,the objective function thus ensures not only that the energy consumption is minimal, but also that the size of the battery is within a reasonable range:
Jcost＝min costbat+∫Pbatdt
costbat＝wb*sbat
wherein costbat,wbThe cost and cost factor of the battery.
Discretizing the data in a time domain, and converting an objective function into:
and delta t is a sampling time interval, and N is the number of sampling points.
Finally, it is noted that the above-mentioned preferred embodiments illustrate rather than limit the invention, and that, although the invention has been described in detail with reference to the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention as defined by the appended claims.

Claims (7)

1. The pure electric vehicle double-motor arrangement and torque optimization method based on the convex optimization algorithm is characterized in that: the method comprises the following steps:
s1: establishing a longitudinal dynamic model of the automobile according to the parameters of the automobile;
s2: selecting the circulation working condition of the automobile, and calculating the required torque T of the automobile according to the selected circulation working conditiondem(k) Required power Pdem(k) Maximum required torque Tdem,maxAnd maximum power demand Pdem,max；
S3: under the assumption of steamOn the premise that the capacity of the vehicle battery meets the dynamic requirement, according to Tdem,maxAnd Pdem,maxSelecting the motor size and the battery size of the automobile;
s4: carrying out convex optimization processing on a motor and a battery of the automobile through a convex optimization algorithm;
s5: the working states of all parts of the automobile transmission system are restrained;
s6: a cost objective function is determined.
2. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 1, characterized in that: in step S1, the longitudinal dynamics model of the vehicle is established as follows:
wherein, Ft(k) Which represents the traction of the vehicle,showing the air resistance of the vehicle during travel, cdIs the coefficient of air resistance, AfIs the windward area of the automobile, rho is the air density, v is the running speed of the automobile, k represents the running time of the automobile, g is the gravity acceleration, crThe rolling resistance coefficient of the road, β the road gradient, a the acceleration of the vehicle during driving, mtotRepresenting the mass of the car.
3. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 2, characterized in that: in step S2, the required torque T of the vehicle is calculateddem(k) Required power Pdem(k) Maximum required torque Tdem,maxAnd maximum power demand Pdem,maxComprises the following steps:
Pdem(k)＝Ft(k)*v(k)
Tdem(k)＝Ft(k)*rwheel
Tdem,max＝max(Tdem(k))
Pdem,max＝max(Pdem(k))
wherein, Ft(k) Is the traction of the vehicle at time k, v (k) is the speed of the vehicle at time k, rwheelIs the wheel radius of the automobile.
4. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 3, characterized in that: the motor size and the battery size of the automobile are selected in step S3 to satisfy:
TEM2,max>TEM1,max
PEM2,max>PEM1,max
TEM1,max+TEM2,max≥Tdem,max
Pbat,max≥Pdem,max
wherein, TEM2,maxIs the maximum output torque, T, of the rear wheel motor of the vehicleEM1,maxIs the maximum output torque, P, of the motor of the front wheel of the automobileEM2,maxIs the maximum output power, P, of the rear wheel motor of the vehicleEM1,maxFor the maximum output power, P, of the motor of the front wheel of the vehiclebat,maxThe maximum output power of the battery.
5. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 4, characterized in that: in step S4, the convex optimization processing is:
VOC(k)＝b0*SOC(k)+b1
wherein, PEMi,loss(k) The loss power of the motor at time k, aij(i 1,2, j 1,2,3) is a coefficient of power loss, VOCIs the open circuit voltage of the battery, TEMi(k) (i is 1,2) is the output of the front and rear wheel motors at time kTorque, b0,b1To fit the coefficients of the battery voltage, which are constant values, SOC (k) is the state of charge of the automotive battery at time k.
6. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 5, characterized in that: step S5, the method for restraining the working states of all parts of the automobile transmission system specifically comprises the following steps:
TEMi(k)∈[TENi,min,TEMi.max]
Pbat(k)∈[Pbat,min,Pbat.max]*sbat
Ebat∈[SOCmin,SOCmax]*Voc*Q*sbat
sbat∈[sbat,min,sbat,max]
wherein T isEMi(k) For the output torque of the front and rear wheel motors of the vehicle at time k, Pbat(k) Is the power of the battery at time k, EbatFor storing the charge of the battery, Pbat,min,Pbat.maxMinimum and maximum values of battery power, SOCmin,SOCmaxMinimum and maximum values of the battery state of charge, V, respectivelyocIs the open circuit voltage of the battery, Q is the capacity of the battery, sbatIs the size factor, s, of the batterybat,min,sbat,maxRespectively, the minimum and maximum values of the battery size factor.
7. The pure electric vehicle double-motor arrangement and convex optimization algorithm-based torque optimization method according to claim 6, characterized in that: the cost objective function in step S6 is:
Jcost＝min costbat+∫Pbatdt
costbat＝wb*sbat
wherein, costbatTo the cost of the battery, wbIs the cost factor of the battery.
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CN110203075A (en) * 2019-05-31 2019-09-06 武汉理工大学 A kind of four-wheel hub motor Vehicular system power matching method
CN110936824A (en) * 2019-12-09 2020-03-31 江西理工大学 Electric automobile double-motor control method based on self-adaptive dynamic planning
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CN109299567A (en) * 2018-10-22 2019-02-01 重庆大学 One kind is towards energy-efficient numerically controlled lathe main transmission design optimization method
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