Vehicle mass estimation method and vehicle mass estimation system

Abstract

The present invention includes: a first step in which the longitudinal acceleration of a vehicle is detected by a longitudinal acceleration sensor; a second step in which, by inputting a drive force into a vehicle model that comprises an equation representing the relationships of longitudinal acceleration, drive force of the vehicle, vehicle mass, and acceleration error occurring in the longitudinal acceleration sensor and having the vehicle mass and the acceleration error as state variables, an estimated value for the longitudinal acceleration expected to be sensed by the longitudinal acceleration sensor and preliminary estimated values for the state variables are calculated; a third step in which estimated values for the state variables are calculated on the basis of the preliminary estimated values and the difference between the estimated value for the longitudinal acceleration and a detected value for the longitudinal acceleration sensed by the longitudinal acceleration sensor; and a fourth step in which the state variables in the equation are updated using the estimated values for the state variables. If the rate of change of a first parameter that is correlated with the drive force is equal to or greater than a first threshold value, the third step and the fourth step are executed; and if the rate of change of the first parameter is less than the first threshold value, the third step and the fourth step are halted.

Description

Vehicle mass estimation method and vehicle mass estimation system

[0001] The present invention relates to a vehicle mass estimation method and a vehicle mass estimation system.

[0002] JP 4926258B discloses a technique for calculating rotational acceleration from the rotational speed of a vehicle's wheels, and estimating vehicle mass as a regression coefficient when linear regression of rotational acceleration and driving force is performed based on a Kalman filter from the vehicle's driving force and rotational angular velocity in accordance with the equation of motion of vehicle driving force = tire rotational acceleration x vehicle mass. JP 4583028B also discloses a similar technique.

[0003] However, the above prior art is a control that prevents the influence of road surface gradient on the estimation of vehicle mass by estimating road surface gradient during driving using a method similar to that for estimating vehicle mass. Therefore, when the rate of change of driving force information is small, it becomes difficult to accurately distinguish between the influence of changes in vehicle mass and the influence of changes in road surface gradient, and the accuracy of estimating vehicle mass decreases.

[0004] Therefore, an object of the present invention is to provide a vehicle mass estimation method and a vehicle mass estimation system that ensure the estimation accuracy of the vehicle mass.

[0005] According to one aspect of the present invention, the method includes: a first step of detecting longitudinal acceleration of the vehicle using a longitudinal acceleration sensor; a second step of calculating an estimated value of longitudinal acceleration expected to be detected by the longitudinal acceleration sensor and a priori estimated value of the state variable by inputting the driving force into a vehicle model having an equation representing the relationship between the longitudinal acceleration, the driving force of the vehicle, the vehicle mass, and an acceleration error generated in the longitudinal acceleration sensor, the equation having the vehicle mass and the acceleration error as state variables; a third step of calculating an estimated value of the state variable based on the prior estimated value and a difference between the estimated value of longitudinal acceleration and a detected value of longitudinal acceleration detected by the longitudinal acceleration sensor; and a fourth step of updating the state variable in the equation using the estimated value of the state variable. Steps three and four are executed when a rate of change of a first parameter correlated with the driving force is equal to or greater than a predetermined first threshold, and steps three and four are stopped when the rate of change of the first parameter is lower than the first threshold.

[0006] FIG. 1 is a block diagram showing the basic configuration of an electric vehicle system to which the vehicle mass estimation method of this embodiment is applied. FIG. 2 is a flowchart showing the flow of processing performed by a motor controller. FIG. 3 is a diagram showing an example of an accelerator opening-torque table. FIG. 4 is a block diagram for explaining the vehicle mass estimation processing. FIG. 5 is a block diagram for explaining the input correction unit. FIG. 6 is a diagram showing the determination flow of the calculation permission determination unit. FIG. 7 is a block diagram for explaining the mass estimation calculation unit. FIG. 8 is a time chart when the driving force change is small. FIG. 9 is a time chart when the driving force change is large.

[0007] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0008] [System Configuration of Electric Vehicle 10] Figure 1 is a block diagram showing the basic configuration of an electric vehicle system to which the vehicle mass estimation method of this embodiment is applied. The electric vehicle 10 is a vehicle that has a motor 18 as part or all of the vehicle's drive source and can run using the driving force of the motor 18, and includes electric vehicles and hybrid vehicles. Note that the electric vehicle 10 shown in Figure 1 is a 2WD vehicle using the motor 18 as its drive source, but the invention can also be applied to 2WD vehicles using an engine as their drive source, and 4WD vehicles using either the motor 18 or an engine as their drive source.

[0009] Digital signals indicating vehicle conditions such as the longitudinal acceleration of the vehicle, vehicle speed V, accelerator opening APO, rotor phase α of motor 18, and three-phase AC currents iu, iv, and iw of motor 18 are input to motor controller 12 (control device). Based on the input signals, motor controller 12 generates PWM signals tu, tv, and tw for controlling motor 18. In addition, motor controller 12 generates drive signals for inverter 16 in accordance with the generated PWM signals tu, tv, and tw.

[0010] The inverter 16 converts the direct current supplied from the battery 14 into alternating current by turning on / off two switching elements (e.g., power semiconductor elements such as IGBTs and MOS-FETs) provided for each phase, and supplies the desired current to the motor 18.

[0011] The motor 18 (three-phase AC motor) generates driving force using the AC current supplied from the inverter 16, and transmits the driving force to left and right drive wheels 24 a, 24 b via a reducer 20 and a drive shaft 22. When the motor 18 is rotated by the drive wheels 24 a, 24 b while the vehicle is running, it generates regenerative driving force, thereby recovering the kinetic energy of the vehicle as electrical energy. In this case, the inverter 16 converts the AC current generated during regenerative operation of the motor 18 into DC current and supplies it to the battery 14.

[0012] The current sensor 26 detects three-phase AC currents iu, iv, and iw flowing through the motor 18. However, since the sum of the three-phase AC currents iu, iv, and iw is zero, the currents of any two phases may be detected and the current of the remaining phase may be calculated.

[0013] The rotation sensor 28 is, for example, a resolver or an encoder, and detects the rotor phase α of the motor 18 .

[0014] Although not shown in the figure, the electric vehicle system of this embodiment is equipped with a steering angle sensor that detects the steering angle of the vehicle and a brake fluid pressure sensor that detects the brake fluid pressure of the friction brake. Information on the steering angle and information on the brake fluid pressure are input to the motor controller 12.

[0015] 2 is a flowchart showing the flow of processing performed by the motor controller 12. The processing from S201 to S206 is constantly executed at regular intervals while the electric vehicle system is running.

[0016] In the input process of S201, signals required for the control calculations described below are input to the motor controller 12. Here, the longitudinal acceleration (m / s ２ ), vehicle speed V (km / h), accelerator opening APO (%), and rotor phase α (rad) of the motor 18. Also input are the rotation speed N (rpm) of the motor 18, three-phase AC currents iu, iv, and iw flowing through the motor 18, and the DC voltage value Vdc (V) of the battery 14.

[0017] Vehicle longitudinal acceleration sensor value a [m / s ２] (detected value) is acquired by a longitudinal acceleration sensor (not shown) that detects longitudinal acceleration occurring in the vehicle.

[0018] The vehicle speed V (km / h) is acquired from a vehicle speed sensor (not shown) or another controller via communication. Alternatively, the motor controller 12 obtains the vehicle speed V (m / s) by multiplying the motor angular velocity detection value ωm by the tire dynamic radius r and dividing the result by the gear ratio of the final gear, and then multiplying the result by 3600 / 1000 for unit conversion to obtain the vehicle speed V (km / h).

[0019] The accelerator opening APO (%) is obtained from an accelerator opening sensor (not shown) or is obtained by communication from another controller (not shown) such as a vehicle controller.

[0020] The rotor phase α (rad) of the motor 18 is acquired from the rotation sensor 28. The motor angular velocity detection value ωm, which is the mechanical angular velocity of the motor 18, is obtained by dividing the rotor angular velocity ω (electrical angle) by the number p of pole pairs of the motor 18. The rotation speed N (rpm) of the motor 18 is obtained by multiplying the obtained motor angular velocity detection value ωm by 60 / (2π). The rotor angular velocity ω is obtained by differentiating the rotor phase α.

[0021] The three-phase AC currents iu, iv, and iw (A) flowing through the motor 18 are acquired from a current sensor 26 .

[0022] The DC voltage value Vdc (V) is detected by a voltage sensor (not shown) provided on a DC power supply line between the battery 14 and the inverter 16. Note that the DC voltage value Vdc (V) may also be detected from a signal related to the power supply voltage value transmitted from a battery controller (not shown).

[0023] In the basic target torque calculation process of S202, the motor controller 12 calculates the basic motor torque command value Tm based on the accelerator opening APO and the motor angular velocity detection value ωm using the accelerator opening-torque table shown in FIG. １ ＊ Set.

[0024] In the vibration suppression control process of S203, the basic motor torque command value Tm calculated in S202 １＊ and the motor angular velocity detection value ωm are input, and the final motor torque command value Tm is calculated to suppress torque transmission system vibration (torsional vibration of the drive shaft, etc.) without sacrificing the response of the drive shaft torque. ２ ＊ Calculate.

[0025] In the vehicle mass estimation process in S204, the final motor torque command value Tm calculated in S203 is used. ２ ＊ and the longitudinal acceleration sensor value a, the vehicle mass M is estimated. The vehicle mass estimation process will be described in detail later.

[0026] In the current command value calculation process of S205, the motor controller 12 calculates the final motor torque command value Tm ２ ＊ , the motor angular velocity detection value ωm, and the d-axis current command value id based on the DC voltage value Vdc. ＊ , q-axis current command value iq ＊ For example, the final motor torque command value Tm ２ ＊ , the rotation speed N of the motor 18, the DC voltage value Vdc, and the d-axis current command value id ＊ and the q-axis current command value iq ＊ A table is prepared in advance that defines the relationship between the d-axis current command value id and the ＊ , q-axis current command value iq ＊ Ask for.

[0027] In the current control of S206, the motor controller 12 controls the d-axis current id and the q-axis current iq by the d-axis current command value id calculated in S205. ＊ and the q-axis current command value iq ＊ To this end, first, the d-axis current id and the q-axis current iq are calculated based on the three-phase AC currents iu, iv, and iw input in S201 and the rotor phase α of the motor 18. Next, the d-axis current command value id ＊ and the d-axis current id, the d-axis voltage command value vd is calculated, and the q-axis current command value iq ＊and the q-axis current iq, a q-axis voltage command value vq is calculated. Note that a decoupling voltage required to cancel out the interference voltage between the d- and q-axis orthogonal coordinate axes may be added to the calculated d-axis voltage command value vd and q-axis voltage command value vq.

[0028] Next, three-phase AC voltage command values ​​vu, vv, and vw are calculated from the d-axis voltage command value vd, the q-axis voltage command value vq, and the rotor phase α of the motor 18. Then, PWM signals tu(%), tv(%), and tw(%) are calculated from the calculated three-phase AC voltage command values ​​vu, vv, and vw and the DC voltage value Vdc. The PWM signals tu, tv, and tw thus calculated are used to open and close the switching elements of the inverter 16, thereby controlling the motor 18 to the final motor torque command value Tm ２ ＊ The motor can be driven at a desired torque indicated by the arrow.

[0029] [Vehicle Model] The vehicle model of this embodiment will be described below. The equation of the vehicle model is shown in equation (1).

[0030] where a is the longitudinal acceleration sensor value, M is the vehicle mass, u is the driving force, and e is the acceleration error.

[0031] The longitudinal acceleration sensor is a sensor that can detect longitudinal acceleration occurring in the vehicle, and therefore the longitudinal acceleration sensor value also includes a gravitational acceleration component due to the gradient.

[0032] The acceleration error e includes an error in the installation of the longitudinal acceleration sensor and an error in the acceleration caused by the tilt of the vehicle due to loading.

[0033] Here, when the transformation of equation (2) is applied to equation (1), equation (3) is obtained.

[0034] When equation (3) is discretized, equation (4) is obtained.

[0035] Reciprocal M of vehicle mass M ｉｎｖ and the acceleration error e, the state variable x ｋ is the inverse of the vehicle mass M ｉｎｖWhen the acceleration error e is taken as the acceleration error, and the observed value y is taken as the longitudinal acceleration sensor value a, the state equation becomes equation (5) and the observation equation becomes equation (6).

[0036] Furthermore, the mean is 0 and the variance is σ ｗ ２ The system noise w is a normal white noise with mean 0 and variance σ ｖ ２ Considering the observation noise v, which is normal white noise, equation (5) becomes equation (7), and equation (6) becomes equation (8).

[0037] However, in equation (7), equations (9) and (10) hold, and in equation (8), equation (11) holds.

[0038] [Vehicle Mass Estimation Process] Fig. 4 is a block diagram for explaining the vehicle mass estimation process. The motor controller 12 (Fig. 1) includes an input correction unit (S401), a calculation permission determination unit (S402), and a mass estimation calculation unit (S403).

[0039] The input correction unit (S401) calculates the vehicle longitudinal acceleration sensor value, the final motor torque command value Tm ２ ＊ , driving wheel speed ω ｗ＿ｄｒｉｖｅ , driven wheel speed ω ｗ＿ｄｒｉｖｅｎ , air resistance / rolling resistance F ｌｏａｄ The vehicle longitudinal acceleration sensor value (corrected) a and the driving force u, which are input signals to the mass estimation calculation unit (S402), are calculated based on the above. The details of the input correction unit (S401) will be described with reference to FIG.

[0040] The calculation permission determination unit (S402) determines the final motor torque command value Tm ２ ＊ , the steering angle, and the braking amount, a calculation permission flag is calculated to determine whether the calculation of the mass estimation calculation unit (S403) is permitted or not. Details of the calculation permission determination unit (S402) will be described with reference to FIG. 6. The final motor torque command value Tm ２ ＊is a parameter that is converted into a driving force u and input to a vehicle model (701) described later, but the braking amount and steering angle are parameters that are not subject to input to the vehicle model (701).

[0041] The mass estimation calculation unit (S403) estimates the vehicle mass M and acceleration error e defined in equation (1) based on the driving force u and the vehicle longitudinal acceleration sensor value (after correction) a. Details of the mass estimation calculation unit (S403) will be described using FIG. 7.

[0042] <Input Correction Unit> Fig. 5 is a block diagram for explaining the input correction unit. The input correction unit (S401 in Fig. 4) executes the following steps S501 to S511.

[0043] In S501, the input correction unit calculates the driving wheel speed ω ｗ＿ｄｒｉｖｅ Approximate differentiation is performed to obtain the driving wheel angular acceleration ω ・ ｗ＿ｄｒｉｖｅ Calculate.

[0044] In S502, the input correction unit calculates the driving wheel angular acceleration ω ・ ｗ＿ｄｒｉｖｅ Wheel inertia J ｗ , motor / differential inertia (motor / differential gear inertia) J ｍｅ , wheel radius R ａ The driving force equivalent of the drive wheel inertia is calculated by multiplying the drive wheel inertia by a gain configured as follows:

[0045] In S503, the input correction unit calculates the driven wheel speed ω ｗ＿ｄｒｉｖｅｎ Approximate differentiation is performed to obtain the driven wheel angular acceleration ω ・ ｗ＿ｄｒｉｖｅｎ Calculate.

[0046] In S504, the input correction unit calculates the driven wheel angular acceleration ω ・ ｗ＿ｄｒｉｖｅｎ Wheel inertia J ｗ , wheel radius R ａ The driving force equivalent of the driven wheel inertia is calculated by multiplying the driving force by a gain composed of the following:

[0047] In S505, the input correction unit adds the driving force equivalent value of the driving wheel inertia output in S502 to the driving force equivalent value of the driven wheel inertia output in S504 to calculate the driving force equivalent value of the driving wheel / driven wheel inertia.

[0048] In S506, the input correction unit calculates the air resistance / rolling resistance F ｌｏａｄ A low-pass filter is applied to adjust the phase of the air resistance / rolling resistance F ｌｏａｄ is calculated using equation (12) using the vehicle speed V, and the parameter A ０ , A １ , A ２ The design value or the value identified by experiment is used.

[0049] In S507, the input correction unit corrects the final motor torque command value Tm ２ ＊ A low-pass filter process is performed on the signal for phase adjustment.

[0050] In S508, the input correction unit calculates the final motor torque command value Tm ２ ＊ The gain K, which is the efficiency of the drive source and the drive force transmission system, ｅ Multiply by.

[0051] In S509, the input correction unit calculates the gear ratio N ａｌ and wheel radius R ａ By multiplying the gain composed of the above, the unit is converted into the dimension of driving force.

[0052] In S510, the input correction unit calculates the driving force u by subtracting the output of S505 and the output of S506 from the output of S509.

[0053] In S511, the input correction unit performs low-pass filtering for phase adjustment on the vehicle longitudinal acceleration sensor value, and calculates a vehicle longitudinal acceleration sensor value (corrected) a.

[0054] The time constants τ used in the filter processes of S501, S503, S506, S507, and S511 are all set to the same value to align the phases.

[0055] <Calculation Permission Determination Unit> Fig. 6 is a diagram showing the flow of determination by the calculation permission determination unit. The calculation permission determination unit (S402 in Fig. 4) executes the following steps S601 to S606.

[0056] In S601, the calculation permission determination unit determines the final motor torque command value Tm ２ ＊ (first parameter) with a predetermined time constant τ １ The torque change rate is calculated by approximately differentiating the time derivative (s) and the time constant τ １ a low-pass filter (1 / (τ １ s+1)) and the final motor torque command value Tm ２ ＊ The output obtained by inputting the above is the torque change rate.

[0057] In S602, the calculation permission determination unit determines whether the absolute value of the torque change rate is equal to or greater than a torque change rate threshold (first threshold). If the absolute value of the torque change rate is equal to or greater than the torque change rate threshold, it is determined that there is a torque change, and the process proceeds to S603. If the absolute value of the torque change rate is smaller than the torque change rate threshold, it is determined that there is no torque change, and the process proceeds to S606. In S603, the calculation permission determination unit determines whether the absolute value of the steering angle (second parameter) is equal to or less than a steering angle threshold (second threshold). If the absolute value of the steering angle is equal to or less than the steering angle threshold, it is determined that steering is not occurring, and the process proceeds to S604. If the absolute value of the steering angle is greater than the steering angle threshold, it is determined that steering is occurring, and the process proceeds to S606. The steering angle (second parameter) is a parameter that is not subject to input to the vehicle model (S701), and is used to calculate the estimated value x^ of the state variable xk. ｋ｜ｋ The amount of operation of a friction brake included in the vehicle also corresponds to the second parameter.

[0058] In S604, the calculation permission determination unit determines whether the braking amount (third parameter) is equal to or less than the braking amount threshold (third threshold). If the braking amount is equal to or less than the braking amount threshold, it is determined that braking is not being performed, and the process proceeds to S605. If the braking amount is greater than the braking amount threshold, it is determined that braking is being performed, and the process proceeds to S606. Note that the braking amount (third parameter) is a parameter that is not subject to input to the vehicle model (S701), and is not included in the estimated value x^ of the state variable xk. ｋ｜ｋ The braking amount includes the operation amount of the friction brake and the regenerative braking amount generated by the motor 18.

[0059] In S605, the calculation permission determination unit determines that calculation is permitted, and sets the calculation permission flag to "HIGH."

[0060] In S606, the calculation permission determination unit determines that calculation is not permitted, and sets the calculation permission flag to "LOW."

[0061] In addition, the time constant τ １ The torque change rate threshold (first threshold), steering angle threshold (second threshold), and braking amount threshold (third threshold) are set based on experimental results, taking into account the degree of influence of the vehicle mass M on the estimated value. The braking amount is the total braking amount including the braking amount due to the friction brake and the braking amount due to the regenerative brake.

[0062] By performing the above processing, the estimation accuracy of the vehicle mass M can be maintained at a predetermined level.

[0063] <Mass Estimation Calculation Unit> Figure 7 is a block diagram for explaining the mass estimation calculation unit. The mass estimation calculation unit (S403 in Figure 4) executes S701 to S705 shown below.

[0064] In S701, the mass estimation calculation unit calculates the state variable x by processing the equations (5) and (6) (or the equations (7) and (8)) using the driving force u as an input value. ｋ The prior estimate of x^ ｋ｜ｋ－１ and calculate the estimated value a^ of the longitudinal acceleration that is expected to be detected by the vehicle longitudinal acceleration sensor. ｋ｜ｋ－１ is the state variable x in equations (5) and (7). ｋ＋１The estimated value a^ of the longitudinal acceleration detected by the vehicle longitudinal acceleration sensor is calculated using the observed value y ｋ This becomes:

[0065] In S702, the mass estimation calculation unit outputs the difference obtained by subtracting the estimated value a^ of the longitudinal acceleration detected by the vehicle longitudinal acceleration sensor from the vehicle longitudinal acceleration sensor value (after correction) a.

[0066] In S703, the mass estimation calculation unit calculates the output value of S702 by applying a correction gain K Ｋ By multiplying by ｋ The prior estimate of x^ ｋ｜ｋ－１ A correction amount for correcting the above is calculated.

[0067] Correction gain K Ｋ When the Kalman filter algorithm is used, it is found by successively calculating the equations (13), (14), and (15).

[0068] where P is the error covariance matrix, K Ｋ is the Kalman gain, Q is the covariance matrix for the system noise, and R is the covariance matrix for the observation noise. Ｋ is updated within the algorithm using the driving force u as an input value, but Q and R are set arbitrarily, so they are set taking into consideration noise contained in the sensors used for the input and observed values ​​and any errors that may occur. The initial value of P is also set taking into consideration the magnitude of the initial estimation error.

[0069] A covariance matrix is ​​a matrix of covariances between vector elements. The larger the covariance, the larger the error involved in the state transition and observation. In this case, the autocovariance (the diagonal components of the covariance matrix) is important among the covariances. This is because the acceleration error e, which is a state variable, and the reciprocal M of the vehicle mass M ｉｎｖ are independent of each other. That is, Q is given by equation (16) and R is given by equation (17).

[0070] Here, q ｅis the autocovariance of the acceleration error e, q Ｍｉｎｖ is the autocovariance of the vehicle mass M, r ａ is the autocovariance of the longitudinal acceleration sensor value a. ｅ , q Ｍｉｎｖ , and r ａ is estimated by experiment or prior knowledge. For example, Q depends on the sampling rate, and R depends on the noise characteristics of the sensor.

[0071] In addition, the correction gain K Ｋ When the algorithm of the recursive least squares method with forgetting factor is used, it can be found by sequentially calculating the equations (18), (19), and (20).

[0072] where λ is the forgetting factor.

[0073] In S704, the mass estimation calculation unit calculates the state variable x ｋ The prior estimate of x^ ｋ｜ｋ－１ is corrected with the output value of S603, the state variable x ｋ The estimated value of x^ ｋ｜ｋ Here, the state variable x ｋ The component of the acceleration error e and the vehicle mass M are ｉｎｖ Therefore, the estimated value of the vehicle mass M can be calculated using equation (2).

[0074] In S705, the mass estimation calculation unit calculates the state variable x ｋ The estimated value of x^ ｋ｜ｋ Then, the past value of the state variable x is sampled, and the process returns to S601. ｋ The estimated value of x^ ｋ｜ｋ The past value of is the state variable x in equations (5)-(8). ｋ This becomes:

[0075] By sequentially repeating the processes of S701 to S705, the state variable x ｋ The estimated value of x^ ｋ｜ｋ By updating the above, it is possible to calculate an accurate estimate of the vehicle mass M.

[0076] However, the mass estimation calculation unit executes the above steps S701 to S705 when the calculation permission flag input from the calculation permission determination unit (S402) is "HIGH." If the calculation permission flag is "LOW," the mass estimation calculation unit does not execute steps S701 to S705 (especially steps S703 to S705), and only calculates the error covariance matrix P and the state variables x ｋ The estimated value of x^ ｋ｜ｋ holds the previous value.

[0077] [Time Chart] Fig. 8 is a time chart when the change in driving force is small. Fig. 9 is a time chart when the change in driving force is large. In both Figs. 8 and 9, the state variable x ｋ The estimated value of x^ ｋ｜ｋ The estimated value of the vehicle mass M is calculated by calculating

[0078] In both Figures 8 and 9, it is assumed that the vehicle starts traveling on a flat road at time t0, reaches a predetermined vehicle speed at time t1, continues traveling at a constant speed thereafter, and then enters a slope from the flat road at time t2.

[0079] In either case, there is no deviation between the estimated value (initial value) of the vehicle mass M at time t0 and the true value of the vehicle mass M, and similarly, there is no deviation between the estimated value (initial value) of the acceleration error e at time t0 and the true value of the acceleration error e.

[0080] Then, an offset is intentionally added to the true value of the acceleration error e at time t3, and an offset is intentionally added to the true value of the vehicle mass M at time t4.

[0081] The final target torque (final motor torque command value Tm ２ ＊ ) takes a high value when the vehicle starts traveling, then rapidly decreases to maintain a predetermined minimum value, and at time t2, it becomes a predetermined value higher than the minimum value according to the gradient of the slope, and thereafter, it keeps the predetermined value. Here, the final target torque is a final motor torque command value Tm ２ ＊In the case of a vehicle that runs on an engine, this corresponds to an engine torque command value that is issued to the engine.

[0082] At time t2, the vehicle enters a slope from a flat road. At this time, during the transition time until the final target torque transitions from the minimum value to the predetermined value, the state variable x ｋ The estimated value of x^ ｋ｜ｋ Furthermore, since the vehicle mass M is estimated from changes in the longitudinal acceleration sensor value a and the driving force u (final target torque) during the transition time, there is no need to estimate the vehicle mass M and the gradient separately, and there is no interference between the calculation processes of the estimated values ​​of the vehicle mass M and the gradient when the gradient changes, which would result in a deterioration in accuracy.

[0083] However, when an offset is applied to the true value of the acceleration error e at time t3, the final target torque (final motor torque command value Tm ２ ＊ ) is smaller than, for example, the torque change rate threshold (first threshold), a discrepancy occurs between the estimated value of vehicle mass M and the true value of vehicle mass M, and similarly a discrepancy occurs between the estimated value of acceleration error e and the true value of acceleration error e, which is never resolved.

[0084] Furthermore, when an offset is applied to the true value of the vehicle mass M at time t4, the final target torque (final motor torque command value Tm ２ ＊ ) is smaller than, for example, the torque change rate threshold (first threshold), a discrepancy occurs between the estimated value of vehicle mass M and the true value of vehicle mass M, and similarly a discrepancy occurs between the estimated value of acceleration error e and the true value of acceleration error e, which is never resolved.

[0085] The final target torque shown in Fig. 9 is obtained by superimposing a pulsating component that oscillates at a predetermined frequency and a predetermined amplitude on the final target torque shown in Fig. 8. Therefore, due to this pulsating component, the state variable x ｋ The estimated value of x^ ｋ｜ｋFurthermore, since the vehicle mass M is estimated from changes in the longitudinal acceleration sensor value a and the driving force u (final target torque) over the entire time range shown in Figure 9, there is no need to estimate the vehicle mass M and the gradient separately, and there is no interference between the calculation processes of the estimated values ​​of the vehicle mass M and the gradient when the gradient changes, which would result in a deterioration in accuracy.

[0086] Therefore, even if an offset is applied to the true value of the acceleration error e at time t3, the final target torque (final motor torque command value Tm ２ ＊ ) is equal to or greater than the torque change rate threshold (first threshold), for example. Therefore, even if a deviation occurs between the estimated value of vehicle mass M and the true value of vehicle mass M at time t3, the estimated value immediately converges to the true value, and similarly, even if a deviation occurs between the estimated value of acceleration error e and the true value of acceleration error e, the estimated value immediately converges to the true value.

[0087] Furthermore, even if an offset is applied to the true value of the vehicle mass M at time t4, the final target torque (final motor torque command value Tm ２ ＊ ) is equal to or greater than the torque change rate threshold (first threshold), for example. Therefore, even if a deviation occurs between the estimated value of vehicle mass M and the true value of vehicle mass M at time t4, the estimated value immediately converges to the true value, and similarly, even if a deviation occurs between the estimated value of acceleration error e and the true value of acceleration error e, the estimated value immediately converges to the true value.

[0088] As shown in FIG. 8, when the change in the driving force u (final target torque) is small, the state variable x ｋ The estimated value of x^ ｋ｜ｋ When the calculation is performed, the estimated value x^ ｋ｜ｋ The difference between the true value and the actual value becomes large, and the estimation accuracy decreases.

[0089] Therefore, in this embodiment, the final target torque (final motor torque command value Tm ２ ＊ ) is equal to or greater than the torque change rate threshold (first threshold), the state variable x ｋ The estimated value of x^ ｋ｜ｋCalculate the estimated value x^ ｋ｜ｋ The state variable x of the vehicle model (S701) is calculated as follows: ｋ is updated, and the final target torque (final motor torque command value Tm ２ ＊ ) is lower than the torque change rate threshold (first threshold), ｋ The estimated value of x^ ｋ｜ｋ The calculation of the estimated value x^ is stopped. ｋ｜ｋ The state variable x of the vehicle model (S701) ｋ This stops updating the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ This distinguishes between when to perform updates and when not.

[0090] Therefore, the driving force u (final motor torque command value Tm ２ ＊ ) changes significantly ｋ The estimated value of x^ ｋ｜ｋ By calculating the state variable x ｋ The estimated value of x^ ｋ｜ｋ This can ensure that the estimation accuracy of the vehicle mass M is maintained at a predetermined level.

[0091] In addition, when the vehicle is traveling at a constant speed and the true value of the vehicle mass M actually changes, as in the case of time t4 in FIGS. 8 and 9, the driving force u (final motor torque command value Tm ２ ＊ ) also changes, so that the state variable x ｋ The estimated value of x^ ｋ｜ｋ That is, the estimated value of the vehicle mass M can be estimated with high accuracy.

[0092] Furthermore, if a disturbance (such as steering or hydraulic braking) that is not taken into account in the vehicle model (S701) is applied, the accuracy of the mass estimation value will be degraded. However, in this embodiment, when no disturbance is applied, the error covariance matrix P is updated and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the state variable x of the vehicle model (S701)ｋ When the disturbance is applied, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the update of the state variables of the vehicle model (S701) are stopped, and the state variable x ｋ This keeps the previous value of the state variable x when updating is resumed. ｋ The estimated value of x^ ｋ｜ｋ The state variable x is calculated in such a way that the estimation error of ｋ The estimated value of x^ ｋ｜ｋ This ensures the accuracy of the estimation.

[0093] [Effects of this embodiment] The vehicle mass estimation method of this embodiment includes the following steps: a first step of detecting the longitudinal acceleration of the vehicle (longitudinal acceleration sensor value a) using a longitudinal acceleration sensor (not shown); and a second step of calculating the relationship between the longitudinal acceleration (longitudinal acceleration sensor value a), the driving force u of the vehicle, the vehicle mass M, and the acceleration error e generated in the longitudinal acceleration sensor (not shown) by using equations (5) and (6), or equations (7) and (8) which express the relationship between the vehicle mass M and the acceleration error e in the longitudinal acceleration sensor (not shown). ｋ By inputting the driving force u into a vehicle model (S701) having an equation, an estimated value a^ of longitudinal acceleration detected by a longitudinal acceleration sensor (not shown) and a state variable x ｋ The prior estimate of x^ ｋ｜ｋ－１ and a second step of calculating the prior estimate x^ ｋ｜ｋ－１ and the difference between the estimated value a^ of the longitudinal acceleration and the detected value of the longitudinal acceleration (longitudinal acceleration sensor value a) detected by the longitudinal acceleration sensor, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and a third step of calculating the state variable x ｋ The estimated value of x^ ｋ｜ｋ The state variable x in the equation ｋ and a fourth step of updating a first parameter (final motor torque command value Tm ２ ＊ , engine torque command value) is equal to or greater than a predetermined first threshold value, the third and fourth steps are executed, and the first parameter (final motor torque command value Tm ２ ＊, engine torque command value) is lower than a first threshold value, the third step and the fourth step are stopped.

[0094] By the above method, the state variable x ｋ The estimated value of x^ ｋ｜ｋ The estimated value of vehicle mass M can be calculated by extracting the component of vehicle mass M from the above. Furthermore, since the above method estimates vehicle mass M from changes in the longitudinal acceleration sensor value a and driving force u (final target torque), there is no need to estimate vehicle mass M and gradient separately, and there is no interference between the calculation process of the estimated value of vehicle mass M and the estimated value of gradient when the gradient changes, which would result in a deterioration in accuracy. Driving force u (final motor torque command value Tm ２ ＊ , engine torque command value) does not change, the state variable x ｋ The vehicle mass M and the acceleration error e, which are components of ｋ In order to estimate the state variable x ｋ The estimated value of x^ ｋ｜ｋ Therefore, when there is a change in the driving force u, the estimation accuracy of the state variable x ｋ The estimated value of x^ ｋ｜ｋ and calculate the state variable x of the vehicle model (S701). ｋ is updated, and if there is no change in the driving force u, the estimated value x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ While stopping the update of the vehicle model (S701), the state variable x ｋ By retaining the previous value of the state variable x when updating is resumed, ｋ The estimated value of x^ ｋ｜ｋ The estimated value x^ is calculated by reducing the estimation error of ｋ｜ｋ This ensures the accuracy of the estimation.

[0095] In this embodiment, in the second step, the driving force u is sequentially input to the vehicle model (S701) to obtain the estimated value a^ of the longitudinal acceleration and the preliminary estimated value x^ ｋ｜ｋ－１ and are sequentially calculated, and the (pre-estimated value x^ is calculated based on the sequentially calculated estimated value a^ of the longitudinal acceleration and the detected value of the longitudinal acceleration (longitudinal acceleration sensor value a). ｋ｜ｋ－１and a difference between an estimated value a^ of the longitudinal acceleration detected by a longitudinal acceleration sensor (not shown) and a detected value of the longitudinal acceleration detected by the longitudinal acceleration sensor (longitudinal acceleration sensor value a) is sequentially calculated, and in a third step, the difference between the sequentially calculated prior estimated value x^ ｋ｜ｋ－１ and the state variable x based on the difference ｋ The estimated value of x^ ｋ｜ｋ In the fourth step, the state variables x ｋ The estimated value of x^ ｋ｜ｋ The state variable x in the equation ｋ is updated sequentially.

[0096] By using the above method, it is possible to successively reduce the modeling error in the vehicle model (S701) and accurately estimate the vehicle mass M, and when there is a change in the driving force u, it is possible to accurately estimate the state variable x ｋ The estimated value of x^ ｋ｜ｋ and calculate the state variable x of the vehicle model (S701). ｋ is updated, and if there is no change in the driving force u, the estimated value x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ The update of the vehicle model (S701) is stopped and the state variable x ｋ By retaining the previous value of the state variable x when updating is resumed, ｋ The estimated value of x^ ｋ｜ｋ The estimated value x^ is calculated by reducing the estimation error of ｋ｜ｋ This ensures the accuracy of the estimation.

[0097] In this embodiment, in the third step, the prior estimate x^ ｋ｜ｋ－１ and a correction gain K including an error covariance matrix P having the driving force u as an input value for the difference (between the estimated value a^ of the longitudinal acceleration and the detected value of the longitudinal acceleration (longitudinal acceleration sensor value a)). Ｋ and the state variable x ｋ The estimated value of x^ ｋ｜ｋ The first parameter (final motor torque command value Tm ２ ＊ , engine torque command value) is equal to or greater than a first threshold value, the error covariance matrix P is updated using the driving force u, and the first parameter (final motor torque command value Tm ２＊ , engine torque command value) is lower than a first threshold value, the update of the error covariance matrix P is stopped.

[0098] By using the above method, when there is a change in the driving force u, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ If there is no change in the driving force u, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the update of the state variables of the vehicle model (S701) are stopped, and the state variable x ｋ This keeps the previous value of the state variable x when updating is resumed. ｋ The estimated value of x^ ｋ｜ｋ This can further reduce the estimation error.

[0099] In this embodiment, the first parameter (final motor torque command value Tm ２ ＊ , engine torque command value) is calculated by time differentiation and a predetermined time constant τ １ and a function (S601) which is the product of the low-pass filter having the first parameter (final motor torque command value Tm ２ ＊ , engine torque command value) is input and calculated as the output obtained.

[0100] By the above method, the first parameter (final motor torque command value Tm ２ ＊ , engine torque command value) can be calculated.

[0101] In this embodiment, the torque command value (final motor torque command value Tm ２ ＊ , engine torque command value).

[0102] With the above configuration, the driving force u can be calculated without adding a sensor for detecting the driving force u.

[0103] In this embodiment, when the value of a second parameter (steering amount, friction brake operation amount) that is correlated with vehicle operation and is not subject to input into the vehicle model (S701) is equal to or greater than a predetermined second threshold, steps 3 and 4 are stopped, and when the value of the second parameter is lower than the second threshold, steps 3 and 4 are executed.

[0104] By the above method, when disturbances (steering amount, friction brake operation amount) not included in the vehicle model (S701) are not applied, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ When the disturbance is applied, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the update of the state variables of the vehicle model (S701) are stopped, and the state variable x ｋ This keeps the previous value of the state variable x when updating is resumed. ｋ The estimated value of x^ ｋ｜ｋ The state variable x is calculated in such a way that the estimation error of ｋ The estimated value of x^ ｋ｜ｋ This ensures the accuracy of the estimation.

[0105] In this embodiment, when the value of a third parameter (regenerative braking amount of motor 18, friction brake operation amount) that is correlated with vehicle braking and is not subject to input into the vehicle model (S701) is equal to or greater than a predetermined third threshold, steps 3 and 4 are stopped, and when the value of the third parameter is lower than the third threshold, steps 3 and 4 are executed.

[0106] In the case of a vehicle using a motor 18 as a drive source, the state variables can be estimated with high accuracy not only in power running but also in regenerative braking. On the other hand, in trailer towing, some trailers are equipped with their own brakes to prevent the vehicle from being pushed by the trailer when the vehicle is decelerating, but the trailer brakes become a disturbance for the estimation calculation. Therefore, when braking by regenerative braking or friction braking is not working, the error covariance matrix P is updated and the state variables x ｋ The estimated value of x^ ｋ｜ｋand the state variable x of the vehicle model (S701) ｋ When the braking is applied, the error covariance matrix P is updated, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and the update of the state variables of the vehicle model (S701) are stopped, and the state variable x ｋ This keeps the previous value of the state variable x when updating is resumed. ｋ The estimated value of x^ ｋ｜ｋ The state variable x is calculated in such a way that the estimation error of ｋ The estimated value of x^ ｋ｜ｋ This ensures the accuracy of the estimation.

[0107] The vehicle mass estimation system of this embodiment includes a longitudinal acceleration sensor (not shown) for detecting longitudinal acceleration of the vehicle, a driving force calculation unit (S510) for calculating a driving force u of the vehicle, and a state variable x (equation (5) and (6), or equation (7) and (8)) that expresses the relationship between the longitudinal acceleration, the driving force u, the vehicle mass M, and an acceleration error e that occurs in the longitudinal acceleration sensor (not shown). ｋ The equation is expressed as follows: when the driving force u is input, the estimated value a^ of longitudinal acceleration is assumed to be detected by a longitudinal acceleration sensor (not shown), and the state variable x ｋ The prior estimate of x^ ｋ｜ｋ－１ and a vehicle model (S701) for calculating the prior estimated value x^ ｋ｜ｋ－１ and the difference between the estimated value a^ of the longitudinal acceleration and the detected value of the longitudinal acceleration (longitudinal acceleration sensor value a) detected by the longitudinal acceleration sensor, and the state variable x ｋ The estimated value of x^ ｋ｜ｋ and a state variable estimation unit (S704) that calculates the state variable x ｋ The estimated value of x^ ｋ｜ｋ The state variable x in the equation ｋ is updated, and the parameter correlated with the driving force u (final motor torque command value Tm ２ ＊ , engine torque command value) is equal to or greater than a predetermined threshold value (first threshold value), the state variable estimation unit (S704) estimates the state variable x ｋ The estimated value of x^ ｋ｜ｋand the vehicle model (S701) calculates the state variable x ｋ is updated, and the parameter (final motor torque command value Tm ２ ＊ , engine torque command value) is lower than a threshold value (first threshold value), the state variable estimation unit (S704) ｋ The estimated value of x^ ｋ｜ｋ The calculation of the vehicle model (S701) is stopped and the state variable x ｋ Stop updating.

[0108] With the above configuration, the state variable x ｋ The estimated value of x^ ｋ｜ｋ The estimated value of vehicle mass M can be calculated by extracting the component of vehicle mass M from the above. Furthermore, with the above configuration, vehicle mass M is estimated from changes in the longitudinal acceleration sensor value a and driving force u (final target torque), so there is no need to estimate vehicle mass M and gradient separately, and there is no interference between the calculation process of the estimated value of vehicle mass M and the estimated value of gradient when the gradient changes, which causes a deterioration in accuracy. Driving force u (final motor torque command value Tm ２ ＊ , engine torque command value) does not change, the state variable x ｋ The vehicle mass M and the acceleration error e, which are components of ｋ In order to estimate the state variable x ｋ The estimated value of x^ ｋ｜ｋ Therefore, with the above configuration, when there is a change in the driving force u, the estimation accuracy of the state variable x ｋ The estimated value of x^ ｋ｜ｋ and calculate the state variable x of the vehicle model (S701). ｋ is updated, and if there is no change in the driving force u, the estimated value x^ ｋ｜ｋ and the state variable x of the vehicle model (S701) ｋ While stopping the update of the vehicle model (S701), the state variable x ｋ By retaining the previous value of the state variable x when updating is resumed, ｋ The estimated value of x^ ｋ｜ｋ The estimated value x^ is calculated by reducing the estimation error of ｋ｜ｋThis ensures the accuracy of the estimation.

[0109] Although the embodiments of the present invention have been described above, the above embodiments merely illustrate some of the application examples of the present invention, and it is not intended that the technical scope of the present invention be limited to the specific configurations of the above embodiments.

Claims

1. A vehicle mass estimation method comprising: a first step of detecting the longitudinal acceleration of a vehicle using a longitudinal acceleration sensor; a second step of calculating an estimated value of the longitudinal acceleration expected to be detected by the longitudinal acceleration sensor and a priori estimated value of the state variable by inputting the driving force into a vehicle model having an equation that represents the relationship between the longitudinal acceleration, the driving force of the vehicle, the vehicle mass, and an acceleration error generated in the longitudinal acceleration sensor, the equation having the vehicle mass and the acceleration error as state variables; a third step of calculating an estimated value of the state variable based on the priori estimated value and the difference between the estimated value of the longitudinal acceleration and the detected value of the longitudinal acceleration detected by the longitudinal acceleration sensor; and a fourth step of updating the state variable in the equation using the estimated value of the state variable, wherein the third and fourth steps are executed when the rate of change of a first parameter correlated to the driving force is equal to or greater than a predetermined first threshold, and the third and fourth steps are stopped when the rate of change of the first parameter is lower than the first threshold.

2. A vehicle mass estimation method as described in claim 1, wherein in the second step, the estimated value of the longitudinal acceleration and the pre-estimated value are sequentially calculated by sequentially inputting the driving force into the vehicle model, and the difference is sequentially calculated based on the sequentially calculated estimated value of the longitudinal acceleration and the detected value of the longitudinal acceleration; in the third step, the estimated value of the state variable is sequentially calculated based on the sequentially calculated pre-estimated value and the difference; and in the fourth step, the state variable in the equation is sequentially updated by the sequentially calculated estimated value of the state variable.

3. A vehicle mass estimation method as described in claim 1 or claim 2, wherein in the third step, an estimate of the state variable is calculated based on the prior estimate and a value obtained by multiplying the difference by a correction gain including an error covariance matrix with the driving force as an input value, and the error covariance matrix is ​​updated using the driving force when the rate of change of the first parameter is equal to or greater than the first threshold, and the updating of the error covariance matrix is ​​stopped when the rate of change of the first parameter is lower than the first threshold.

4. A vehicle mass estimation method according to claim 1 or 2, wherein the rate of change of the first parameter is calculated as an output obtained by inputting the first parameter into a function that is the product of a time derivative and a low-pass filter having a predetermined time constant.

5. A vehicle mass estimation method according to claim 1 or 2, wherein the driving force is calculated based on a torque command value output to a driving source of the vehicle.

6. A vehicle mass estimation method according to claim 3, wherein the third and fourth steps are stopped when a value of a second parameter that is correlated with the operation of the vehicle and is not subject to input to the vehicle model is equal to or greater than a predetermined second threshold, and the third and fourth steps are executed when the value of the second parameter is lower than the second threshold.

7. A vehicle mass estimation method according to claim 3, wherein the third and fourth steps are stopped when the value of a third parameter that is correlated with braking of the vehicle and is not subject to input to the vehicle model is equal to or greater than a predetermined third threshold, and the third and fourth steps are executed when the value of the third parameter is lower than the third threshold.

8. A vehicle model including: a longitudinal acceleration sensor that detects longitudinal acceleration of a vehicle; a driving force calculation unit that calculates a driving force of the vehicle; a vehicle model having an equation that represents the relationship between the longitudinal acceleration, the driving force, vehicle mass, and an acceleration error generated in the longitudinal acceleration sensor, the equation having the vehicle mass and the acceleration error as state variables, the vehicle model calculating an estimated value of the longitudinal acceleration that is expected to be detected by the longitudinal acceleration sensor when the driving force is input, and a priori estimated value of the state variable; and a state variable estimation unit that calculates the estimated value of the state variable based on the prior estimated value and a difference between the estimated value of the longitudinal acceleration and the detected value of the longitudinal acceleration detected by the longitudinal acceleration sensor, wherein the vehicle model updates the state variable in the equation using the estimated value of the state variable, when a rate of change of a parameter correlated with the driving force is equal to or greater than a predetermined threshold, the state variable estimator calculates an estimate of the state variable and the vehicle model updates the state variable in the equation; and when the rate of change of the parameter is lower than the threshold, the state variable estimator stops calculating the estimate of the state variable and the vehicle model stops updating the state variable in the equation.

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