Vehicle control method and vehicle control device

Abstract

To provide a vehicle control method and a control device capable of performing suitable slip control of a driving wheel by estimating vehicle body speed with higher accuracy.SOLUTION: A vehicle control method includes: determining a plurality of data regions I to III divided according to a driven state of an electric vehicle; acquiring acceleration / deceleration speed (a) of the electric vehicle when a motor is driven based on a motor torque command value; holding driving force F determined based on the acquired acceleration / deceleration speed (a) and the motor torque command value in each of the data regions I to III; and calculating a vehicle mass estimation value with reference to the acceleration / deceleration speed (a1, a2, and a3) and the driving force (F1, F2, and F3) held in each of the data regions I to III.SELECTED DRAWING: Figure 13

Description

Technical Field

[0001] The present invention relates to a vehicle control method and a vehicle control device.

Background Art

[0002] Conventionally, a technique for estimating the mass during the running of a vehicle has been known, assuming a scene where the mass of the entire vehicle varies according to the loading amount of luggage or the like. Patent Document 1 discloses a technique for estimating the mass of a vehicle based on the acceleration and driving force of the vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] On the other hand, the inventors of the present invention have focused on the fact that in existing mass estimation methods, the accuracy of the mass estimation value is not sufficiently ensured depending on the driving state of the vehicle, and there is a risk that the reliability of vehicle behavior control (slip control, etc.) based on the mass estimation value may decrease.

[0005] In view of such circumstances, an object of the present invention is to provide a vehicle control method and a vehicle control device that can estimate the mass of a vehicle with higher accuracy during the running of the vehicle.

Means for Solving the Problems

[0006] According to an aspect of the present invention, there is provided a vehicle control method for driving a motor based on a predetermined motor torque command value and calculating a vehicle mass estimation value based on the driving state of an electric vehicle having the motor as a driving power source.

[0007] In this vehicle control method, a plurality of data areas divided according to the driving state of the electric vehicle are defined. When driving the motor based on the motor torque command value, the acceleration and deceleration of the electric vehicle are obtained, and the driving force determined based on the obtained acceleration and deceleration and the motor torque command value is held in each data area. A vehicle mass estimated value is calculated by referring to the acceleration and deceleration and the driving force held in each data area.

Effect of the Invention

[0008] According to the present invention, the mass of the vehicle can be estimated with higher accuracy during the running of the vehicle.

Brief Description of the Drawings

[0009]

Figure 1

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Figure 7

Figure 8

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Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Figure 16

Figure 17

Figure 18

Figure 19

Mode for Carrying Out the Invention

[0010] Hereinafter, embodiments of the present invention will be described.

[0011] Figure 1 is a block diagram for explaining the main configuration of an electric vehicle system 100 to which the vehicle control method according to the present embodiment is applied.

[0012] Note that the electric vehicle in the present embodiment is an automobile equipped with a drive motor 4 (electric motor) as a drive source of the vehicle and capable of traveling by the driving force of the drive motor 4, and includes an electric vehicle and a hybrid vehicle. In particular, the electric vehicle system 100 of the present embodiment applied to an electric vehicle has two drive motors 4 (front drive motor 4f and rear drive motor 4r). Hereinafter, the configuration of the electric vehicle system 100 will be described in more detail.

[0013] As shown in FIG. 1, the electric vehicle system 100 includes a front drive system fds, a rear drive system rds, a battery 1, and a motor controller 2.

[0014] The front drive system fds is provided with various sensors and actuators for controlling a front drive motor 4f that drives front drive wheels 9f (left front drive wheel 9fL and right front drive wheel 9fR).

[0015] On the other hand, the rear drive system rds is provided with various sensors and actuators for controlling a rear drive motor 4r that drives rear drive wheels 9r (left rear drive wheel 9rL and right rear drive wheel 9rR).

[0016] The front drive system fds and the rear drive system rds are each individually controlled by the motor controller 2.

[0017] The battery 1 functions as a power source for supplying (discharging) drive power to each drive motor 4, and is connected to an inverter 3 (front inverter 3f and rear inverter 3r) so that it can be charged by receiving regenerative power from each drive motor 4.

[0018] The motor controller 2 is a computer composed of, for example, a central processing unit (CPU), a read-only memory (ROM), a random access memory (RAM), and an input / output interface (I / O interface).

[0019] Signals of various vehicle variables indicating the vehicle state, such as the accelerator opening Apo, the rotor phase α of the drive motor 4 (front rotor phase α f and rear rotor phase α r ), and the current I m of the drive motor 4 (front motor current I mf and rear motor current I mr ), are input as digital signals to the motor controller 2.

[0020] The motor controller 2 generates a PWM signal for controlling each drive motor 4 based on the input signal. Further, a drive signal for each inverter 3 is generated according to each generated PWM signal.

[0021] Each inverter 3 has two switching elements (for example, power semiconductor elements such as IGBTs and MOS-FETs) provided corresponding to each phase. In particular, each inverter 3 turns on / off the switching elements according to a command from the motor controller 2, thereby converting the DC current supplied from the battery 1 into an AC current or vice versa, and adjusting the current supplied to each drive motor 4 to a desired value.

[0022] Each drive motor 4 is configured as a three-phase AC motor. Each drive motor 4 (front drive motor 4f and rear drive motor 4r) generates a driving force by the AC current supplied from the corresponding inverter 3 (front inverter 3f and rear inverter 3r), and transmits the driving force to each drive wheel 9 (front drive wheel 9f and rear drive wheel 9r) via the corresponding reduction gear 5 (front reduction gear 5f and rear reduction gear 5r) and each drive shaft 8 (front drive shaft 8f and rear drive shaft 8r).

[0023] Further, when the drive motor 4 rotates being driven by the drive wheels 9 during the running of the vehicle, it generates a regenerative driving force, thereby recovering the kinetic energy of the vehicle as electrical energy. In this case, the inverter 3 converts the AC current generated during regenerative operation into a DC current and supplies it to the battery 1.

[0024] The rotation sensors 6 (front rotation sensor 6f and rear rotation sensor 6r) detect the rotor phase α (front rotor phase α f and rear rotor phase α r ) of the drive motor 4 respectively, and output them to the motor controller 2. The rotation sensor 6 is constituted by, for example, a resolver or an encoder.

[0025] The current sensors 7 (front current sensor 7f and rear current sensor 7r) detect the three-phase alternating currents (iu, iv, iw) flowing through each drive motor 4. Since the sum of the three-phase alternating currents (iu, iv, iw) is 0, the current sensors 7 may detect any two-phase currents, and the remaining one-phase current may be obtained by calculation. In particular, the current sensors 7 detect the three-phase alternating current (iu f , iv f , iw f ) flowing through the front drive motor 4f and the three-phase alternating current (iu r , iv r , iw r ) flowing through the rear drive motor 4r.

[0026] <Overall Processing> FIG. 2 is a flowchart for explaining the overall processing of the vehicle control method according to the present embodiment. Each process shown in FIG. 2 is executed by the motor controller 2 (or each inverter 3) at a predetermined calculation cycle.

[0027] In S201, the motor controller 2 performs an input process of acquiring various parameters used for executing the processes after S202 according to the following processes 1 to 3.

[0028] 1. Detection values of each sensor The motor controller 2 acquires the accelerator opening Apo (%), the rotor phase α [rad], the three-phase alternating current (iu, iv, iw) [A] flowing through the drive motor 4, and the DC voltage value Vdc [V] of the battery 1 from the above-described accelerator opening sensor and each sensor (not shown).

[0029] 2. Previous value of the final torque command value T m ** of The motor controller 2 stores the final torque command value T (front final torque command value T m ** (f m and rear final torque command value T ** r m ** ​Obtain the previous value of ().

[0030] 3. Control parameters obtained by calculation Based on each parameter obtained in the above "1.", the motor controller 2 calculates the motor electrical angular velocity ω e [rad / s], the motor rotational speed ω m [rad / s], the motor rotation speed N m [rpm], and the wheel speed ω w [km / h].

[0031] (i) Motor electrical angular velocity ω e The motor controller 2 time-differentiates the rotor phase α (front rotor phase α f and rear rotor phase α r ) to obtain each motor electrical angular velocity ω e (front motor electrical angular velocity ω ef and rear motor electrical angular velocity ω er ).

[0032] (ii) Motor rotational speed ω m The motor controller 2 divides the motor electrical angular velocity ω e by the number of pole pairs of the drive motor 4 to calculate the motor rotational speed ω m (front motor rotational speed ω mf and rear motor rotational speed ω mr ) which is the mechanical angular velocity of the drive motor 4. Note that the relationship between the motor rotational speed ω m and the rotational speed of the drive shaft 8 which is the drive axis is appropriately determined according to the gear ratio of the speed reducer 5. That is, the motor rotational speed ω m is a speed parameter correlated with the rotational speed of the drive shaft 8.

[0033] (iii) Motor rotation speed Nm The motor controller 2 multiplies the motor rotational speed ω m by the unit conversion coefficient (60 / 2π) to obtain the motor rotation speed N m (front motor rotation speed N mf and rear motor rotation speed Nmr ) is calculated.

[0034] (iv) Wheel speed ω w First, the motor controller 2 multiplies the front motor rotation speed ω mf by the tire dynamic radius, and based on the value obtained by this multiplication and the gear ratio of the front speed reducer 5f, calculates the left front drive wheel speed ω wfL and the right front drive wheel speed ω wfR . Also, the motor controller 2 multiplies the rear motor rotation speed ω mr by the tire dynamic radius, and based on the value obtained by this multiplication and the gear ratio of the final gear of the rear speed reducer 5r, calculates the left front drive wheel speed ω wfL and the right front drive wheel speed ω wfR . And in this embodiment, each wheel speed ω w thus obtained is multiplied by the unit conversion coefficient (3600 / 1000) to convert the unit of the wheel speed ω w from [m / s] to [km / h].

[0035] Next, in S202, the motor controller 2 calculates the basic target torque (T mf1 * , T mr1 * ) required by the driver based on the vehicle information.

[0036] Specifically, first, the motor controller 2 refers to the accelerator opening - torque table and calculates the first torque target value T mf , which is the basic target value for the combined torque of the front drive motor 4f and the rear drive motor 4r, based on the accelerator opening Apo and the front motor rotation speed ω m1 * obtained in S201.

[0037] In FIG. 3, an example of the accelerator opening - torque table referred to by the motor controller 2 of this embodiment is shown.

[0038] Next, the motor controller 2 uses this first torque target value Tm1 * Based on the predetermined front and rear motor torque distribution, according to the front target torque command value T mf1 * and the rear target torque command value T mr1 * are calculated.

[0039] FIG. 4 is a block diagram for explaining the calculation of the front target torque command value T mf1 * and the rear target torque command value T mr1 * is a block diagram for explaining the calculation.

[0040] As shown in the figure, the motor controller 2 multiplies the first torque target value T m1 * by the front and rear driving force distribution gains Kf (0 ≤ Kf ≤ 1) and 1 - Kf respectively to obtain the front target torque command value T mf1 * and the rear target torque command value T mr1 * is obtained.

[0041] In S203, the motor controller 2 executes a vehicle body speed estimation process. Specifically, the motor controller 2 uses each wheel speed ω w obtained in S201, the front target torque command value T mf1 * and the rear target torque command value T mr1 * , and the previous value of the front final torque command value T mf ** and the previous value of the rear final torque command value T mr ** to calculate the vehicle body speed estimated value V^. The vehicle body speed estimation process will be described in detail later.

[0042] In S204, the motor controller 2 executes a slip control process. Specifically, the motor controller 2 uses the front target torque command value T mf1 * calculated in S202 and the rear target torque command value Tmr1 * , and based on the vehicle speed estimated value V^ calculated in S203, the target motor rotation speed ω m * (target front motor rotation speed ω mf * and target rear motor rotation speed ω mr * ) are calculated. Further, the motor controller 2 adjusts the front motor rotation speed ω mf and rear motor rotation speed ω mr to match the target front motor rotation speed ω mf * and target rear motor rotation speed ω mr * by correcting the front target torque command value T mf1 * and rear target torque command value T mr1 * to calculate the final torque command value T m ** (front final torque command value T mf ** and rear final torque command value T mr ** ). Note that the slip control process will be described in detail later.

[0043] In S205, the motor controller 2 (or each inverter 3) executes current command value calculation processing. Specifically, the motor controller 2 refers to a predetermined table based on the front final torque command value T mf ** calculated in S204, the rear final torque command value T mr ** , the target front motor rotation speed ω mf * , the target rear motor rotation speed ω mr * , and the DC voltage value V dc acquired in S201 to obtain the dq-axis current target values (i d * , i q *) is calculated. In particular, the motor controller 2 calculates the dq-axis current target values (i d * , i q * ) for the front drive motor 4f, which are the front dq-axis current target values (i df * , i qf * ), and the dq-axis current target values (i d * , i q * ) for the rear drive motor 4r, which are the rear dq-axis current target values (i dr * , i qr * ).

[0044] In S206, the motor controller 2 executes current control arithmetic processing. Specifically, the motor controller 2 first calculates the dq-axis current values (i d , i q ) based on the three-phase AC current values (iu, iv, iw) and the rotor phase α obtained in S201. Next, the motor controller 2 calculates the dq-axis voltage command values (v d , v q ) from the deviation between the dq-axis current values (i d , i q ) and the dq-axis current target values (i d * , i q * ) obtained in S205. In particular, the motor controller 2 calculates the front dq-axis voltage command values (v d , v q ) for the front drive motor 4f, which are the front dq-axis voltage command values (v df , v qf ), and the rear dq-axis voltage command values (v d , v q ) for the rear drive motor 4r, which are the rear dq-axis voltage command values (v dr , v qr ).

[0045] Furthermore, the motor controller 2 calculates the dq-axis voltage command values (v d , vq ) and based on the rotor phase α, calculate the three-phase AC voltage command values (vu, vv, vw). In particular, the motor controller 2 is the front three-phase AC voltage command values (vu, vv, vw) set for the front drive motor 4f, i.e., the front three-phase AC voltage command values (vu f , vv f , vw f ), and the rear three-phase AC voltage command values (vu, vv, vw) which are the three-phase AC voltage command values (vu, vv, vw) set for the rear drive motor 4r f , vv f , vw f ) are calculated.

[0046] Then, the motor controller 2 obtains the PWM signals (tu, tv, tw)[%] based on the calculated three-phase AC voltage command values (vu, vv, vw) and the DC voltage value Vdc. By opening and closing the switching elements of the inverter 3 with the thus obtained PWM signals (tu, tv, tw), the drive motor 4 can be driven with the desired torque indicated by the final torque command value T m ** ).

[0047] Next, the details of the vehicle body speed estimation process in S203 will be described.

[0048] <Vehicle body speed estimation process> First, the transmission characteristics used in the vehicle body speed estimation process in this embodiment will be described based on the model of the vehicle's driving force transmission system.

[0049] 1. Transmission characteristics G mf from the front motor torque command value T mf to the front motor rotational speed ω pff (s) First, in the electric vehicle system 100, the transmission characteristics G mf from the front motor torque command value (hereinafter, also simply referred to as "front motor torque T mf ") to the front motor rotational speed ω pff (s) will be described. This transmission characteristic G pff(s) is used as a vehicle model that models (simulates) the driving force transmission system of a vehicle in vehicle body speed estimation processing. First, the motion equation from the front motor torque T mf to the front motor rotational speed ω mf will be described with reference to FIG. 5.

[0050] FIG. 5 is a diagram modeling the driving force transmission system of the electric vehicle (particularly, a 4WD electric vehicle) of the present embodiment. Each parameter in FIG. 5 is as follows. Note that the auxiliary symbol f indicates the front and r indicates the rear. J mf and J mr : motor inertia J wf and J wr : driving wheel inertia (for one axis) K df and K dr : torsional stiffness of the drive system K tf and K tr : coefficient related to the friction between the tire and the road surface N f and N r : overall gear ratio r f and r r : tire load radius ω mf and ω mr : motor rotational speed ω^ mf and ω^ mr : estimated value of motor rotational speed θ mf and θ mr : motor angle ω wf and ω wr : driving wheel angular velocity θ wf and θ wr : driving wheel angle T mf and T mr : motor torque T df and T dr : drive shaft torque F f and F r : driving force (for two axes) θdf , θ dr : Twist angle of the drive shaft V: Vehicle speed M: Vehicle mass

[0051] As shown in Figure 5, the equations of motion of the 4WD vehicle are represented by the following equations (1) to (11).

[0052]

Equation

[0053] Here, the transmission characteristics from the front motor torque T mf to the front motor rotational speed ω mf are given by the following equation (12) obtained by Laplace-transforming the above equations (1) to (11).

[0054]

Equation

[0055] However, each parameter in equation (12) is represented by the following equations (13) to (17), respectively.

[0056]

Equation

[0057]

Equation

[0058]

Equation

[0059]

Equation

[0060]

Equation

[0061] To examine the poles and zeros of the transfer function shown in Equation (12), factoring Equation (12) with respect to the Laplace operator s results in the following Equation (18).

[0062]

Number

[0063] However, in the equation, "M pff ", "α", "α'", "β", "β'", "ζ pr」 ", "ζ pr '", "ω pr ", "ω pr '", "ζ zr ", "ζ pf ", "ω zf ", and "ω pf " are constants independent of s.

[0064] Here, "α" and "α'", "β" and "β'", "ζ pr " and "ζ pr '", and "ω pr " and "ω pr '" in Equation (18) take values that are extremely close to each other. Therefore, by approximating α ≒ α', β ≒ β', ζ pr ≒ ζ pr ', ω pr ≒ ω pr ', it is possible to consider that a part of the zeros (the values of s for which the numerator becomes 0) and a part of the poles (the values of s for which the denominator becomes 0) approximately coincide with each other. Under this approximation, pole-zero cancellation is performed by canceling the zero term of the numerator and the pole term of the denominator in Equation (18). As a result, a transfer characteristic G pff (s) shown in the following Equation (19) can be constructed.

[0065]

Number

[0066] However, "M" in Equation (19)pff "J" is a constant obtained by appropriately modifying "M" in consideration of the deviation between the assumed zeros and poles in the pole-zero cancellation based on the approximation of each of the above constants. pff」

[0067] As a result, based on the equations of motion of the 4WD vehicle, examining the transfer characteristics from the front motor torque T mf to the front motor rotational speed ω mf up to, G pff (s) can be approximated by a quadratic / cubic equation.

[0068] Here, the reference response for suppressing the torsional vibration caused by the front drive shaft 8f is set as the following equation (20).

[0069]

Equation

[0070] In this case, the feedforward compensator for suppressing the torsional vibration of the front drive system fds can be expressed by the following equation (21).

[0071]

Equation

[0072] 2. Rear motor torque command value T mr (hereinafter, also simply referred to as "rear motor torque T mr ") to the rear motor rotational speed ω mr up to the transfer characteristics G prr (s) Next, in the same way as the method for obtaining the transfer characteristics G mf from the above-mentioned front motor torque T mf to the front motor rotational speed ω pff (s), the transfer characteristics G mr from the rear motor torque T mr to the rear motor rotational speed ω prr (s) are obtained. This transfer characteristic G prr (s) is represented by the following equation (22).​

[0073] [Number]

[0074] Here, the following equation (23) is set as the standard response for suppressing the torsional vibration caused by the rear drive shaft 8r.

[0075] [Number]

[0076] In this case, the feedforward compensator for suppressing the torsional vibration of the rear drive system rds can be expressed by the following equation (24).

[0077] [Number]

[0078] 3. Rear motor torque T mr to the front motor rotational speed ω mf The transfer characteristic G prf (s) The rear motor torque T mr to the front motor rotational speed ω mf The transfer characteristic G prf (s) becomes the following equation (25) obtained by Laplace-transforming the above equations (1) to (11).

[0079] [Number]

[0080] When examining the poles of the transfer function shown in equation (25), it becomes the following equation (26).

[0081] [Number]

[0082] However, since the poles of Equation (26) (``s = -α'' and ``s = -β'') are far from the origin and the dominant poles, the influence on the transfer characteristics represented by G prf (s) is small. Therefore, Equation (26) can be approximated by the transfer function represented by the following Equation (27).

[0083]

Number

[0084] Furthermore, considering the rear vibration control algorithm in the vehicle model G prf (s) (assuming ζ pr ≈ 1), the transfer function shown in the following Equation (28) is obtained.

[0085]

Number

[0086] Also, the transfer function for suppressing the torsional vibration of the front drive system fds from the normalized response of the estimated front motor rotational speed ω^ mf of the front drive system fds is given by the following Equation (29).

[0087]

Number

[0088] 4. Details of the Estimation of the Vehicle Body Speed V Figure 6 is a block diagram for explaining the vehicle body speed estimation process. As shown in the figure, the vehicle body speed estimation process (S203) of the present embodiment includes a wheel speed selection process (S600), a vehicle mass estimation process (S700), and an estimated vehicle speed calculation process (S800).

[0089] Specifically, in the wheel speed selection process (S600), based on the first torque target value T m1 * obtained in S202 above, the left front drive wheel speed ω wfL, the right front drive wheel speed ω wfR , the left rear drive wheel speed ω wrL , and the right rear drive wheel speed ω wrR One of them is selected as the select wheel speed ω w_d and set.

[0090] More specifically, when the first torque target value T m1 * takes a positive value, the left front drive wheel speed ω wfL , the right front drive wheel speed ω wfR , the left rear drive wheel speed ω wrL , and the right rear drive wheel speed ω wrR The smallest value among them is set as the select wheel speed ω w_d to.

[0091] Here, when the first torque target value T m1 * is a positive value, it means that the driving force is input in the forward direction to the 4WD vehicle (during acceleration). During acceleration, if any of the drive wheels 9 is in an over-rotating state, it is assumed that the speed of the over-rotating drive wheel 9 will be greater than the speed of the other drive wheels 9. Based on such a situation, in this embodiment, when the first torque target value T m1 * is a positive value, the smallest value among the values of the above-mentioned wheel speeds ω w is selected, so that a select wheel speed ω w_d closer to the actual vehicle body speed V can be set.

[0092] On the other hand, when the first torque target value T m1 * takes a negative value, the left front drive wheel speed ω wfL , the right front drive wheel speed ω wfR , the left rear drive wheel speed ω wrL , and the right rear drive wheel speed ω wrR The largest value among them is set as the select wheel speed ω w_d to.

[0093] That is, the first torque target value T m1 *When it is a negative value, it means that a driving force is input in the reverse direction to the 4WD vehicle (during deceleration). During deceleration, if any of the drive wheels 9 is in a state of insufficient rotation, it is assumed that the speed of the drive wheel 9 in this insufficient rotation state will be lower than the speed of the other drive wheels 9. Therefore, during deceleration, contrary to acceleration, by selecting the largest value from among the values of the respective wheel speeds ω w a select wheel speed ω w_d close to the actual vehicle body speed V can be set.

[0094] Note that when the first torque target value T m1 * is 0, either the smallest value or the largest value among the values of the respective wheel speeds ω w can be selected as the select wheel speed ω w_d .

[0095] Also, the select wheel speed ω w_d to be selected is not limited to the smallest value or the largest value among the above-described drive wheel speeds ω wr , and other values such as the second largest value or the third largest value may be selected according to the driving scene of the vehicle.

[0096] Next, in the vehicle mass estimation process (S700), using the select wheel speed ω w_d set in S600, the detected value of the acceleration a of the electric vehicle (hereinafter referred to as "acceleration detection value a _d "), the brake hydraulic pressure P B , the front final torque command value T mf ** (especially its previous value), and the rear final torque command value T mr ** (especially its previous value) as inputs, a vehicle mass estimated value M^ and a gradient resistance estimated value d^ are calculated. Note that the acceleration detection value a _d is obtained by, for example, an acceleration sensor (not shown), and the brake hydraulic pressure P B can be obtained by a brake hydraulic pressure sensor (not shown).

[0097] FIG. 7 is a block diagram for explaining the details of the vehicle mass estimation process. As shown in the figure, the vehicle mass estimation process (S700) includes a total driving force calculation process (S701), a running resistance calculation process (S702), a driving force calculation process (S703), a mass estimation execution determination process (S704), and a mass / resistance calculation process (S705).

[0098] In the total driving force calculation process (S701), the front driving force F mf ** is calculated by multiplying the front final torque command value T f by a gain determined according to the gear ratio and the dynamic tire radius of the front drive system. Also, the rear driving force F mr ** is calculated by multiplying the rear final torque command value T r by a gain determined according to the gear ratio and the dynamic tire radius of the rear drive system. Further, the sum of the front driving force F f and the rear driving force F r is taken to calculate the total driving force F to of the electric vehicle.

[0099] In the running resistance calculation process (S702), using the selected wheel speed ω w_d set in S600 as an input, the resistance component R acting on the electric vehicle is calculated by referring to a predetermined running resistance map. Here, the resistance component R is a parameter that occurs in the running scene of the electric vehicle and indicates an external force that inhibits the change in acceleration a with respect to the torque command. The resistance component R is determined by comprehensively considering, for example, air resistance, rolling resistance of the tires, various inertias, various efficiencies, and various losses.

[0100] In the driving force calculation process (S703), the resistance component R is subtracted from the total driving force F to to calculate the driving force (hereinafter referred to as "driving force F") acting on the acceleration a of the electric vehicle.

[0101] In the mass estimation execution determination process (S704), the acceleration detection value a _d , the steering angle θ s , and the brake hydraulic pressure P BBased on the input, a determination is made as to whether to perform the estimation of the vehicle mass M (whether to execute the calculation of the estimated vehicle mass M^). Further, in the mass / resistance calculation process (S705), based on the determination result in the mass estimation execution determination process (S704), with reference to the acceleration detection value a _d and the driving force F, the respective holding values [(a1, F1), (a2, F2), (a3, F3)] stored in each of the data areas I to III described later are determined, and the estimated vehicle mass M^ and the estimated gradient resistance d^ are calculated from the respective holding values.

[0102] FIG. 13 is a flowchart showing the details of the mass estimation execution determination process and the mass / resistance calculation process.

[0103] As shown in the figure, in S1301, input processing of various parameters (acceleration detection value a _d , steering angle θ s , and brake hydraulic pressure P B ) is executed.

[0104] Then, in S1302, with reference to the steering angle θ s and the brake hydraulic pressure P B , a determination is made as to whether to perform mass estimation. More specifically, when the steering angle θ s is less than or equal to a predetermined value and the brake hydraulic pressure P B is less than or equal to a predetermined value (especially 0), it is determined to perform mass estimation and the processing after S1303 is executed. On the other hand, if not, it is determined not to perform mass estimation and this process is terminated (the previous values are maintained as the estimated vehicle mass M^ and the estimated gradient resistance d^).

[0105] Furthermore, in S1303 to S1308, the respective holding values [(a1, F1), (a2, F2), (a3, F3)] stored in each of the data areas I to III are updated according to the respective magnitude relationships between the acceleration detection value a _d and each predetermined threshold value a th1_d , a th2_d , a th3_d (a th1_d < a th2_d < a th3_d ).

[0106] More specifically, when the acceleration detection value a _d is greater than the third threshold value a th3_d (when S1305 is Yes), data area III is selected, and the stored values (a3, F3) in data area III are updated with the current acceleration detection value a _d and the driving force F. Note that the initial value of "a3" is set to the third threshold value a th3_d and the initial value of "F3" is determined based on the third threshold value a th3_d and the design mass.

[0107] Also, when the acceleration detection value a _d is greater than the second threshold value a th2_d and less than or equal to the third threshold value a th3_d (when S1304 is Yes and S1305 is No), data area II is selected, and the stored values (a2, F2) in data area II are updated with the current acceleration detection value a _d and the driving force F. Note that the initial value of "a2" is set to the second threshold value a th2_d and the initial value of "F2" is determined based on the second threshold value a th2_d and the design mass.

[0108] Furthermore, when the acceleration detection value a _d is greater than the first threshold value a th1_d and less than or equal to the second threshold value a th2_d (when S1303 is Yes and S1304 is No), data area I is selected, and the stored values (a1, F1) in data area I are updated with the current acceleration detection value a _d and the driving force F. Note that the initial value of "a1" is set to the first threshold value a th1_d and the initial value of "F1" is determined based on the first threshold value a th1_d and the design mass.

[0109] Note that when the acceleration detection value a _d is less than or equal to the first threshold value a th1_d , mass estimation is not performed, and this process is terminated (the previous values are maintained for the vehicle mass estimation value M^ and the gradient resistance estimation value d^).

[0110] According to the algorithms of S1303 to S1308 described above, the respective holding values [(a1, F1), (a2, F2), (a3, F3)] stored in each data region I to III are determined according to the current acceleration a and driving state (driving force F) of the electric vehicle.

[0111] Note that the holding values [(a1, F1), (a2, F2), (a3, F3)] of each data region I to III may be calculated from the population of the region. More specifically, for example, the acceleration detection value a _d when it is greater than the third threshold value a th3_d the combinations of the acceleration detection value a _d and the driving force F are stored for a plurality of cycles (a plurality of samples), and values (such as average values) obtained by performing predetermined statistical processing on the combinations of the plurality of acceleration detection values a _d and the driving force F may be used as the holding value (a3, F3) in the data region III. The same applies to the holding value (a1, F1) in the data region I and the holding value (a2, F2) in the data region II.

[0112] Next, in S1309, an estimated vehicle mass M^ and an estimated gradient resistance d^ are calculated from the respective holding values [(a1, F1), (a2, F2), (a3, F3)] using the least squares method. Hereinafter, the details of the calculation of the estimated vehicle mass M^ and the estimated gradient resistance d^ will be described.

[0113] First, assuming that there is no wheel slip, the dynamics in the longitudinal direction of the electric vehicle can be expressed by the following equation (30).

[0114]

Equation

[0115] Note that the definitions of the respective parameters in Equation (30) are as follows.

[0116]

Equation

[0117] Hereinafter, for convenience of description, the second derivative with respect to time of x representing the vehicle acceleration in Equation (30) is denoted as "d 2 x / dt 2 ". Further, the driving force F acting on the acceleration a corresponds to the first to fifth terms (i.e., the terms excluding ε) on the right side of Equation (30).

[0118] Here, the acceleration sensor has an offset error even when the electric vehicle pitches forward and backward or is in a stopped state in the mounted state or towing state of the electric vehicle. Therefore, in Equation (30), an error factor ε affected by vehicle pitch and the like is considered.

[0119] And when obtaining the vehicle mass estimated value M^, it is necessary to remove the influence of the error factor ε. Therefore, in the present embodiment, a linear regression algorithm (particularly the least squares method) is executed using each holding value [(a1, F1), (a2, F2), (a3, F3)] as measurement data. More specifically, in the following Equation (31), the holding values (a1, a2, a3) are used as the terms of the following (d 2 / dt 2 ), and the vehicle mass estimated value M^ and the error factor ε are calculated so that the residual S is minimized when the holding values (F1, F2, F3) are applied to the term of "F i " respectively. i

[0120]

Equation

[0121] Here, the vehicle mass estimated value M^ is determined as the slope of the regression line determined by Equation (31), and the error factor ε is determined as the intercept thereof. That is, the vehicle mass estimated value M^ and the error factor ε can be obtained by the following Equation (32).

Equation

[0122] ​In particular, in the present embodiment, by setting "n" in Equation (32) to 3 and applying the holding values F1, F2, and F3 related to the driving force F to the parts of (d 2 / dt 2 )1, (d 2 / dt 2 )3, and (d 2 / dt 2 )3 respectively, the vehicle mass estimated value M^ and the error factor ε can be obtained. Also, in the present embodiment, the error factor ε obtained in this way is output as the gradient resistance estimated value d^.

[0123] Returning to FIG. 6, in S800 (estimated vehicle speed calculation process), the motor controller 2 calculates the vehicle body speed estimated value V^ from the vehicle mass estimated value M^ and the gradient resistance estimated value d^.

[0124] FIG. 8 is a block diagram for explaining the estimated vehicle speed calculation process.

[0125] As shown in the figure, in S801, the motor controller 2 subtracts the gradient resistance estimated value d^ from the sum of the previous value of the front final torque command value T mf ** and the previous value of the rear final torque command value T mr ** to obtain the corrected total torque command value T m_c .

[0126] That is, this corrected total torque command value T m_c is a value obtained by eliminating the influence of the road surface gradient resistance on the total torque command value (that is, the torque command value acting on the acceleration of the vehicle).

[0127] Then, in S802, the motor controller 2 performs a filtering process on the calculated corrected total torque command value T m_c using the above-described vehicle response G r (s) to obtain the vehicle body speed estimated value V^.

[0128] Here, when it is determined that the vehicle is not in a slip state (overspeed state or underspeed state) in the front slip determination process of S1001 and the rear slip determination process of S1005 described later, the estimated vehicle body speed V^ obtained by the selected wheel speed ω w_d is initialized.

[0129] That is, when determining the non-overspeed state, it is assumed that the tire and the road surface are in a gripping state. Therefore, it is considered that the actual vehicle body speed V and the selected wheel speed ω w_d are substantially the same, and the selected wheel speed ω w_d is directly set as the estimated vehicle body speed V^.

[0130] In the above-described estimated vehicle speed calculation process, as shown in FIG. 8, an example of calculating the estimated vehicle body speed V^ by filtering processing using the simple vehicle model and the vehicle response G r (s) was described. However, the vehicle model used in the estimated vehicle speed calculation process is not limited to the above-described mode, and other vehicle models may be used.

[0131] FIG. 9 shows a block diagram for explaining an example of the estimated vehicle speed calculation process when using a more detailed vehicle model. In particular, the transfer characteristics from the motor torque T m to the estimated vehicle body speed V^ are determined based on the above-described equations of motion (1) to (11) of the 4WD vehicle, and are equivalent to the transfer characteristics from the front motor torque T mf and the rear motor torque T mr to the vehicle body speed V.

[0132] By the processes described above, the estimated vehicle body speed V^ can be calculated using the selected wheel speed ω w_d , the front final torque command value T mf ** (especially its previous value), and the rear final torque command value T mr ** (especially its previous value) to calculate the estimated vehicle mass M^ and the estimated gradient resistance d^, and calculating the estimated vehicle body speed V^ from these values.

[0133] <Slip control process> FIG. 10 is a block diagram for explaining the slip control process (S204).

[0134] As shown in the figure, the slip control process includes a front slip determination process (S1001), a front target rotation speed regulation process (S1002), a front slip control process (S1003), a front torque switching process (S1004), a rear slip determination process (S1005), a rear target rotation speed regulation process (S1006), a rear slip control process (S1007), and a rear torque switching process (S1008).

[0135] Specifically, in the front slip determination process (S1001), based on the front motor rotation speed ω obtained in S201 mf , the estimated vehicle speed V^ calculated in S203, and the front target torque command value T calculated in S202 mf1 * , the slip determination of the front drive wheel 9f is performed.

[0136] More specifically, first, it is determined whether the front target torque command value T mf1 * is a positive value (whether the vehicle is accelerating or decelerating). If this determination is affirmative, the time derivative value dω of the front motor rotation speed ω mf is subtracted from the time derivative value of the estimated vehicle speed V^, which is the vehicle acceleration estimated value dV^ / dt. mf / dt

[0137] And when the value obtained by this subtraction (hereinafter, also referred to as the "slip determination value") is equal to or greater than a predetermined threshold Th1, it is determined that the front drive wheel 9f is in a slip state. On the other hand, when the slip determination value is less than the threshold Th1, it is determined that the front drive wheel 9f is in a non-slip state.

[0138] Note that the above threshold Th1 is set such that, during vehicle acceleration, the front motor rotation speed ω is such that it can be actually determined that the front drive wheel 9f is in a slip state mfIt is a value determined from the viewpoint of whether the change rate of [the relevant factor] deviates from the change rate of the estimated vehicle body speed V^.

[0139] On the other hand, when the front target torque command value T mf1 * is a negative value (when the vehicle is decelerating), the slip determination value is calculated in the same way. And when the slip determination value is less than or equal to a predetermined threshold Th2, it is determined that the front driving wheels 9f are in a slip state. On the other hand, when the slip determination value exceeds the threshold Th2, the motor controller 2 determines that the front driving wheels 9f are in a non-slip state.

[0140] Note that the above threshold Th2 is a value determined from the viewpoint of whether the change rate of the front motor rotational speed ω mf deviates from the change rate of the estimated vehicle body speed V^ to such an extent that it can be determined that the front driving wheels 9f are actually in a slip state when the vehicle is decelerating.

[0141] Next, in the front target rotational speed regulation process (S1002), based on the estimated vehicle body speed V^ calculated in S203 and the front target torque command value T mf1 * calculated in S202, the target front motor rotational speed ω mf * is determined.

[0142] In particular, different processes are performed when the front target torque command value T mf1 * is a positive value and when it is not. First, the process when the front target torque command value T mf1 * is a positive value will be described.

[0143] FIG. 11 is a block diagram for explaining the front target rotational speed regulation process when the front target torque command value T mf1 * is a positive value.

[0144] As shown in the figure, the front target torque command value T mf1* When it is a positive value, based on the vehicle body speed estimated value V^ calculated in S203, refer to a predetermined map to calculate the target slip vehicle speed V s * (S1101). The calculated target slip vehicle speed V s * is added to the vehicle body speed estimated value V^ (S1102), and the obtained value is multiplied by a gain (N f / r f ) to obtain the target front motor rotational speed ω mf * .

[0145] Note that when the front target torque command value T mf1 * is a negative value, similarly calculate the target slip vehicle speed V s * , subtract the target slip vehicle speed V from the vehicle body speed estimated value V^ s * , and multiply the obtained value by a gain (N f / r f ) to obtain the target front motor rotational speed ω mf * .

[0146] Next, in the front slip control process (S1003), the front motor rotational speed ω mf obtained in S201 is made to follow the target front motor rotational speed ω mf * calculated in S1002, and the front slip control torque command value T mf1_s * is calculated. The front slip control process will be described in more detail.

[0147] FIG. 12 is a block diagram for explaining the front slip control process. The transfer functions constituting the transfer characteristics of each block shown in FIG. 12 are defined as follows.

[0148] R1(s) is the canonical model of the feedback system of the model matching control, and specifically is represented by the following equation (33).

[0149]

Mathematics

[0150] R2(s) is the canonical model of the entire system of model matching control, and specifically, it is represented by the following equation (34).

Mathematics

[0151] Note that H(s) is a robust filter represented by the following equation (35).

[0152]

Mathematics

[0153] H act (s) is a filter that takes into account the actuator response delay represented by the following equation (36).

Mathematics

[0154] Also, the constant "T" in the block of "e -sTs " is a time constant considering the delay in control calculation or the delay in sensor detection.

[0155] Note that the front slip control process shown in Fig. 12 is a so-called robust model matching type of feedback control, but it is not limited to this, and other feedback controls such as PI control may be adopted.

[0156] Returning to Fig. 10, in the front torque switching process (S1004), when it is determined in the front slip determination process in S1001 that the front drive wheel 9f is in a slip state, the front slip control torque command value T mf1_s * is set as the front final torque command value T mf **Set it as

[0157] On the other hand, when the motor controller 2 determines that the front drive wheel 9f is in a non-slip state, the front target torque command value T mf1 * is set as the front final torque command value T mf ** Set it as

[0158] Furthermore, in the rear slip determination process (S1005), the rear target rotation speed regulation process (S1006), the rear slip control process (S1007), and the rear torque switching process (S1008), the same processes as the above S1001 to S1004 are executed.

[0159] Specifically, in the rear slip determination process (S1005), it is determined whether the rear drive wheel 9r is in a slip state. Also, in the rear target rotation speed regulation process (S1006), the target rear motor rotation speed ω mr * is regulated. In the rear slip control process (S1007), the rear slip control torque command value T mr is set so that the rear motor rotation speed ω mr * follows the target rear motor rotation speed ω mr1_s * Furthermore, in the rear torque switching process (S1008), when the rear drive wheel 9r is in a slip state, the rear slip control torque command value T mr1_s * is set as the rear final torque command value T mr ** while when the rear drive wheel 9r is in a non-slip state, the rear target torque command value T mr1 * is set as the rear final torque command value T mr ** Set it as

[0160] By executing the slip control process described above, it is possible to realize the driving force control of a 4WD vehicle that can suppress the slip of the drive wheels 9.

[0161] <Control result> Next, the control result by the vehicle control method (example) of the present embodiment will be described while comparing it with a comparative example.

[0162] (Comparative Example 1 and Example 1) FIG. 14 is a time chart showing the change over time of each parameter (particularly the estimated vehicle mass M^) when applied in a scene where an electric vehicle starts and accelerates from a stopped state when the controls of Comparative Example 1 and Example 1 are applied.

[0163] Note that Example 1 assumes a control in which the estimated vehicle mass M^ is calculated by the least squares method using each holding value [(a1, F1), (a2, F2), (a3)] determined by the algorithm shown in FIG. 13 described above. On the other hand, as Comparative Example 1, a control that is different from Example 1 only in that the estimated vehicle mass M^ is calculated by the least squares method from a past history data group without considering the change in the driving state of the electric vehicle during running is assumed.

[0164] As shown in the figure, in Comparative Example 1, it can be seen that the estimated vehicle mass M^ increases with respect to the initial value from time t1 to time t2 and deviates from the actual vehicle mass M. This is considered to be due to an error occurring in the estimation result because the estimated vehicle mass M^ was obtained from a past history data group without considering the driving state of the electric vehicle.

[0165] On the other hand, in Example 1, it can be seen that the estimated vehicle mass M^ generally coincides with the actual vehicle mass M after increasing with respect to the initial value from time t1 to time t2. This is considered to be because the estimated error was reduced by calculating the estimated vehicle mass M^ using each holding value [(a1, F1), (a2, F2), (a3)] determined in consideration of the driving state of the electric vehicle.

[0166] (Comparative Example 2 and Example 2) FIG. 15 is a time chart showing the change over time of each parameter when the control of Comparative Example 2 is applied in a scene where an electric vehicle starts and accelerates from a stopped state. Further, FIG. 15 is a time chart showing the change over time of each parameter when the control of Example 2 is applied in a scene where an electric vehicle starts and accelerates from a stopped state.

[0167] Note that in Example 2, the estimated vehicle mass M^ is calculated by the least squares method using each holding value [(a1, F1), (a2, F2), (a3)] determined by the algorithm shown in FIG. 13 described above, the estimated vehicle body speed V^ is determined from the estimated vehicle mass M^, and further, the motor torque command value (T mf ** , T mr ** ) is obtained by slip control using the estimated vehicle body speed V^. On the other hand, as Comparative Example 2, using the estimated vehicle mass M^ calculated in the same manner as in Comparative Example 1, the motor torque command value (T mf ** , T mr ** ) is obtained by control assumed.

[0168] As can be seen from FIG. 15, in the comparative example, it can be seen that after time t0, the error of the estimated vehicle mass M^ affects and the estimated vehicle body speed V^ deviates from the actual vehicle body speed V. More specifically, the estimated vehicle mass M^ is smaller than the actual vehicle mass M, and the estimated vehicle body speed V^ is estimated to be a value larger than the actual vehicle body speed V. For this reason, based on the estimated vehicle body speed V^ that deviates from the actual vehicle body speed V, the front drive wheel speed ω wf and the rear drive wheel speed ω wr slip control is executed. As a result, it can be seen that from time t0 to time t3, the respective deviations (slip amounts) of the front drive wheel speed ω wf and the rear drive wheel speed ω wr from the actual vehicle body speed V become large, and the desired slip state cannot be controlled.

[0169] In contrast, as can be seen from FIG. 16, in the embodiment, it can be seen that the estimated vehicle mass M^ coincides with the actual vehicle mass M, and thus the estimated vehicle body speed V^ also coincides with the actual vehicle body speed V. Further, as shown in FIG. 17, when the estimated vehicle mass M^ coincides with the actual vehicle mass M, the estimated vehicle body speed V^ coincides with the actual vehicle body speed V, and according to the estimated vehicle body speed V^, the front drive wheel speed ω wf and the rear drive wheel speed ω wr At times t0 to t3 when controlling, it can be seen that the front drive wheel speed ω wf and the rear drive wheel speed ω wr can be controlled to a desired slip state. That is, in the case of the control of the embodiment, even in a driving scene on a low-μ road by an electric vehicle (4WD) equipped with a plurality of drive motors 4f and 4r, the estimated vehicle body speed V^ can be determined with high accuracy to realize a desired slip state (acceleration / deceleration state).

[0170] The operation and effect of the vehicle control method of the present embodiment described above will be described.

[0171] According to the present embodiment, in an electric vehicle having a motor (drive motors 4f and 4r) as a driving power source, a vehicle control method is provided in which the drive motor 4 is driven based on a predetermined motor torque command value (T mf ** , T mr ** ), and an estimated vehicle mass V^ is calculated based on the driving state (acceleration a, driving force F) of the electric vehicle.

[0172] In this vehicle control method, a plurality of data regions I to III divided according to the driving state of the electric vehicle (acceleration a in the present embodiment) are defined, and the acceleration detection value a mf ** , T mr ** ) of the electric vehicle when the drive motor 4 is driven based on the motor torque command value (T _d ) is acquired, and the acquired acceleration detection value a _d and the motor torque command value (T mf ** , T mr **The driving force F determined based on is held in each of the data regions I to III (S1306, S1307, S1308 in FIG. 13), and the vehicle mass estimated value M^ is calculated by referring to the acceleration / deceleration speeds (a1, a2, a3) and the driving forces (F1, F2, F3) held in each of the data regions I to III.

[0173] As a result, the driving force F measured sequentially and the acceleration detection value a at that time _d are held in the data regions I to III divided according to the acceleration a, and the vehicle mass estimated value M^ can be obtained using each of the held values [(a1, F1), (a2, F2), (a3)] held in each of the data regions I to III. That is, it is possible to obtain the vehicle mass estimated value M^ with less bias in the data reflecting the driving state of the electric vehicle in real time.

[0174] Further, in the present embodiment, the vehicle body speed estimated value V^ is calculated based on the vehicle mass estimated value M^, and slip control (S1003, S1004, S1007, S1008) using the vehicle body speed estimated value V^ is executed, and the basic motor torque command value (T mf1 * , T mr1 * ) based on the required driving force for the electric vehicle is used to calculate the motor torque command value (T mf ** , T mr ** ).

[0175] As a result, it is possible to obtain the vehicle body speed estimated value V^ with little deviation from the actual vehicle body speed V using the highly accurate vehicle mass estimated value M^ obtained as described above, and further, by executing slip control for the drive wheels 9f, 9R using this vehicle body speed estimated value V^, the slip state of the drive wheels 9f, 9R can be appropriately controlled.

[0176] Furthermore, in the slip control (S204) of the present embodiment, the slip state of the drive wheels 9f, 9r is determined based on the vehicle body speed estimated value V^, and based on the vehicle body speed estimated value V^ and the slip state, the motor torque command value (T mf ** , Tmr ** ) is calculated, and the vehicle body speed estimated value V^ is calculated based on the motor torque command value (T mf ** , T mr ** ), the estimated vehicle mass M^, and the estimated gradient resistance d^.

[0177] Thereby, while considering the slip state of the drive wheels 9 in the electric vehicle, a specific arithmetic algorithm for obtaining a highly accurate vehicle body speed estimated value V^ from the estimated vehicle mass M^ can be realized.

[0178] Note that each holding value [(a1, F1), (a2, F2), (a3, F3)] is preferably calculated by the population for each data area I to III.

[0179] Thereby, the reliability of each holding value [(a1, F1), (a2, F2), (a3, F3)] can be improved, and the estimated vehicle mass M^ can be determined with higher accuracy.

[0180] Also, in the present embodiment, linear regression (particularly the least squares method) is performed on the acceleration (a1, a2, a3) and the estimated driving force (F1, F2, F3) held in each data area I to III, and the slope of the obtained regression line (linear regression equation) is calculated as the estimated vehicle mass M^.

[0181] Thereby, a specific arithmetic algorithm for appropriately calculating the estimated vehicle mass M^ from each holding value [(a1, F1), (a2, F2), (a3, F3)] is realized.

[0182] Furthermore, in the present embodiment, the resistance component R generated in the driving scene of the electric vehicle is estimated, and the driving force F is calculated by correcting the motor torque command value (T mf ** , T mr ** ) with the resistance component R (S701, S702, S703 in FIG. 7).

[0183] Thereby, the motor torque command value (Tmf ** , T mr ** For the ( ), a driving force F that acts substantially on the acceleration a, with the influence of losses and resistances assumed in the driving scene of the electric vehicle removed, is defined, and from this, an estimated vehicle mass M^ can be obtained. Therefore, the responsiveness and accuracy of the estimated vehicle mass M^ can be further improved.

[0184] Also, in this embodiment, the intercept of the regression line obtained by the least squares method is calculated as the estimated gradient resistance d^.

[0185] Thereby, the estimated gradient resistance d^ required when calculating the estimated vehicle body speed V^ from the estimated vehicle mass M^ can be determined using the regression line (linear regression equation) used when obtaining the estimated vehicle mass M^.

[0186] Furthermore, in this embodiment, a motor controller 2 that functions as a vehicle control device suitable for executing the above vehicle control method is provided.

[0187] In particular, this motor controller 2 includes a setting unit that defines a plurality of data regions I to III divided according to the driving state of the electric vehicle (acceleration a in this embodiment), and a motor torque command value (T mf ** , T mr ** ) based on which an acquisition unit that acquires the acceleration / deceleration (acceleration detection value a _d ) of the electric vehicle when driving the drive motor 4, an acceleration detection value a _d obtained, and a holding unit (S1306, S1307, S1308 in FIG. 13) that holds the driving force F determined based on the motor torque command value (T mf ** , T mr ** ) in each of the data regions I to III, and a calculation unit that calculates the estimated vehicle mass M^ with reference to the acceleration / deceleration (a1, a2, a3) and the driving force (F1, F2, F3) held in each of the data regions I to III.

[0188] [Modification Example] Hereinafter, each modification example (the first to third modification examples) of the vehicle control method and the vehicle control device according to the above-described embodiment will be described. In each modification example, the same reference numerals are assigned to the same elements as those in the above-described embodiment, and the description thereof will be omitted.

[0189] (First Modification Example) FIG. 17 is a block diagram for explaining the main configuration of the electric vehicle system 200 according to this modification example.

[0190] As shown in the figure, the electric vehicle system 200 of this modification example does not include a drive motor 4 at the front of the vehicle, and is configured only by the rear drive system rds.

[0191] The rear drive system rds includes a right rear drive system rdsR and a left rear drive system rdsL.

[0192] The right rear drive system rdsR includes a right rear drive motor 4rR that drives the right rear drive wheel 9rR, and various sensors and actuators for controlling the right rear drive motor 4rR. The left rear drive system rdsL includes a left rear drive motor 4rL that drives the left rear drive wheel 9rL, and various sensors and actuators for controlling the left rear drive motor 4rL. In particular, this electric vehicle system 200 is mounted on a 2WD vehicle equipped with two drive motors 4.

[0193] In the electric vehicle system 200 of this modification example, for example, by making modifications such as setting a suitable vehicle model while replacing the parameters of the front drive system fds and the rear drive system rds in the above-described embodiment with the parameters related to the right rear drive system rdsR and the left rear drive system rdsL, the vehicle control method according to the present invention can be realized.

[0194] For example, the front motor rotation speed ω mf and the rear motor rotation speed ω mr are respectively replaced with the right rear motor rotation speed ω mrRand the left rear motor rotation speed ω mrL while replacing it, the front motor torque command value T mf and the rear motor torque command value T mr are respectively replaced with the right rear motor torque command value T mrR and the left rear motor torque command value T mrL By appropriately changing parameters such as replacement, it is possible to execute the vehicle control method according to the present invention.

[0195] (Second Modification Example) FIG. 18 is a block diagram for explaining the main configuration of the electric vehicle system 300 to which the vehicle control method of this modification example is applied.

[0196] As shown in the figure, the electric vehicle system 300 of this modification example includes a front drive system fds, a right rear drive system rdsR, and a left rear drive motor 4rL. That is, this electric vehicle system 300 includes a total of three drive motors 4, namely, a front drive motor 4f that drives the front drive shaft 8f, a right rear drive motor 4rR that drives the right rear drive wheel 9rR, and a left rear drive motor 4rL that drives the left rear drive wheel 9rL. In particular, this electric vehicle system 300 is mounted on a 4WD vehicle having a total of three drive motors 4.

[0197] In the electric vehicle system 300 of this modification example, for example, while executing the same control method as the above embodiment, by setting an appropriate gain for distributing the parameters set in the rear drive system rds to the right rear drive system rdsR and the left rear drive system rdsL, the vehicle control method according to the present invention can be realized.

[0198] (Third Modification Example)

[0199] FIG. 19 is a block diagram for explaining the main configuration of the electric vehicle system 400 to which the vehicle control method of this modification example is applied.

[0200] As shown in the figure, the electric vehicle system 400 of this modification example includes a front drive system fdsR provided with various sensors and actuators for controlling a right front drive motor 4fR that drives a right front drive wheel 9fR, and a left front drive system fdsL provided with various sensors and actuators for controlling a left front drive motor 4fL that drives a left front drive wheel 9fL.

[0201] Also, the rear drive system rds is also composed of a right rear drive system rdsR and a left rear drive system rdsL. Therefore, the electric vehicle system 400 includes a total of four drive motors 4, namely, a right front drive motor 4fR, a left front drive motor 4fL, a right rear drive motor 4rR, and a left rear drive motor 4rL. That is, the electric vehicle system 300 is mounted on a 4WD vehicle having a total of four drive motors 4.

[0202] In the electric vehicle system 400 of this modification example, for example, while executing the same control method as in the above embodiment, each parameter of the front drive system fds is distributed to the right front drive system fdsR and the left front drive system fdsL by an appropriate distribution gain, and each parameter of the rear drive system rds is distributed to the right rear drive system rdsR and the left rear drive system rdsL by an appropriate distribution gain, whereby the vehicle control method according to the present invention can be realized.

[0203] As described above, the embodiments of the present invention have been described. However, the configurations described in the above embodiments and each modification example merely show a part of the application examples of the present invention, and are not intended to limit the technical scope of the present invention.

[0204] For example, in the above embodiment, mainly, the mass estimation assuming an acceleration scene (acceleration a and torque command value are positive) of the electric vehicle and the slip control using the estimation result were described. However, even in the case of a deceleration scene (acceleration a and torque command value are negative) of the electric vehicle, similarly, the slip control using the mass estimation and the estimation result can be executed.

Description of Symbols

[0205] 1 Battery 2 Motor Controller 3 Inverter 4 Drive Motor 5 Reducer 6 Rotation Sensor 7 Current Sensor 8 Drive Shaft 9 Drive Wheel 100 Electric Vehicle System 200 Electric Vehicle System 300 Electric Vehicle System 400 Electric Vehicle System

Claims

1. In an electric vehicle having a motor as a driving power source, a vehicle control method for driving the motor based on a predetermined motor torque command value and calculating a vehicle mass estimated value based on the driving state of the electric vehicle, comprising: defining a plurality of data regions divided according to the driving state of the electric vehicle; acquiring the acceleration and deceleration of the electric vehicle when the motor is driven based on the motor torque command value; holding the driving force determined based on the acquired acceleration and deceleration and the motor torque command value in each data region; calculating the vehicle mass estimated value with reference to the acceleration and deceleration and the driving force held in each data region; a vehicle control method.

2. The vehicle control method according to claim 1, comprising: calculating a vehicle body speed estimated value based on the vehicle mass estimated value; performing slip control of the driving wheels using the vehicle body speed estimated value, and calculating the motor torque command value from a basic motor torque command value based on a required driving force for the electric vehicle; a vehicle control method.

3. The vehicle control method according to claim 2, comprising: in the slip control: determining the slip state of the driving wheels based on the vehicle body speed estimated value; calculating the motor torque command value based on the vehicle body speed estimated value and the slip state; calculating the vehicle body speed estimated value based on the motor torque command value, the vehicle mass estimated value, and a gradient resistance estimated value; a vehicle control method.

4. The vehicle control method according to claim 1, comprising: calculating the acceleration and deceleration and the driving force held in each data region by a population for each data region; a vehicle control method.

5. The vehicle control method according to claim 1, comprising: performing linear regression on the acceleration and deceleration and the driving force held in each data region, and calculating the slope of the obtained regression line as the vehicle mass estimated value; a vehicle control method.

6. The vehicle control method according to claim 1, comprising: estimating a resistance component generated in the driving scene of the electric vehicle; calculating the driving force by correcting the motor torque command value with the resistance component; a vehicle control method.

7. The vehicle control method according to claim 5, comprising: calculating the intercept of the regression line as a gradient resistance estimated value; a vehicle control method.

8. In an electric vehicle having a motor as a driving power source, a vehicle control device that drives the motor based on a predetermined motor torque command value and calculates an estimated vehicle mass based on the driving state of the electric vehicle, a setting unit that defines a plurality of data regions divided according to the driving state of the electric vehicle; an acquisition unit that acquires the acceleration / deceleration of the electric vehicle when the motor is driven based on the motor torque command value; a holding unit that holds the driving force determined based on the acquired acceleration / deceleration and the motor torque command value in each data region; a calculation unit that calculates the estimated vehicle mass by referring to the acceleration / deceleration and the driving force held in each data region, and a vehicle control device.

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