Vehicle mass estimation method and vehicle mass estimation device

Abstract

This vehicle mass estimation method includes: calculating an estimated acceleration, which is an estimated value of a longitudinal acceleration of a vehicle, on the basis of a driving force generated by a power source for driving the vehicle and a predetermined vehicle model; calculating an error between the estimated acceleration and an actual acceleration, which is the longitudinal acceleration of the vehicle detected by an acceleration sensor; correcting the vehicle model according to the calculated error; and estimating the mass of the vehicle on the basis of the corrected vehicle model. The vehicle mass estimation method includes: acquiring a vehicle body pitch angle θ; correcting the actual acceleration according to the vehicle body pitch angle θ; and calculating the error between the estimated acceleration and the corrected actual acceleration.

Description

Vehicle mass estimation method and vehicle mass estimation device

[0001] The present invention relates to a method for estimating vehicle mass and a vehicle mass estimation apparatus.

[0002] During vehicle operation, various processes are performed, including control of driving and braking forces, and estimation of remaining driving range. In recent years, accurately determining the vehicle's mass has become desirable in order to perform these processes more effectively.

[0003] JP2019-190852A discloses a vehicle weight estimation method comprising the steps of: acquiring the values ​​of the longitudinal G sensors at each of a plurality of waypoints set at predetermined time intervals, and the driving force and driving resistance values ​​acting on the vehicle at each of the plurality of waypoints; and estimating the vehicle weight by referring to the difference between the longitudinal G sensor value at a first waypoint among the plurality of waypoints and the longitudinal G sensor value at a second waypoint different from the first waypoint, the difference between the driving force at the first waypoint and the driving force at the second waypoint, and the difference between the driving resistance value at the first waypoint and one or more types of driving resistance values ​​at the second waypoint. Herein, longitudinal G refers to longitudinal acceleration.

[0004] The aforementioned document claims that this estimation method makes it possible to accurately estimate vehicle weight even when the driving resistance value changes due to changes in steering angle, etc. Furthermore, since the driving resistance value includes air resistance and road surface inclination, it can also handle changes in road surface gradient.

[0005] Incidentally, the estimation method described in the above-mentioned literature ignores the effect of the vehicle body pitch angle, assuming it is sufficiently small. However, pitching behavior that occurs during vehicle acceleration or deceleration affects the values ​​detected by the acceleration sensor, and consequently, the estimated value of the vehicle mass. Therefore, the estimation method described in the above-mentioned literature has room for improvement in terms of estimation accuracy.

[0006] Therefore, the present invention aims to provide a method for estimating the mass of a vehicle with greater accuracy.

[0007] According to one aspect of the present invention, a vehicle mass estimation method is provided, which calculates an estimated acceleration, which is an estimated value of the longitudinal acceleration of a vehicle, based on the driving force generated by a power source for driving a vehicle and a predetermined vehicle model; calculates the error between the estimated acceleration and the actual acceleration, which is the longitudinal acceleration of the vehicle detected by an acceleration sensor; corrects the vehicle model according to the calculated error; and estimates the mass of the vehicle based on the corrected vehicle model. In this method, the vehicle body pitch angle θ is obtained, the actual acceleration is corrected according to the vehicle body pitch angle θ, and the error between the corrected actual acceleration and the estimated acceleration is calculated.

[0008] Figure 1 is a block diagram illustrating the configuration of the vehicle. Figure 2 is a flowchart showing the control routine for drive force control. Figure 3 is a diagram showing an example of an accelerator opening-torque table. Figure 4 is a control block diagram showing the contents of the vehicle mass estimation process. Figure 5 is a control block diagram showing the processing contents of the torque correction unit. Figure 6 is a control block diagram showing the processing contents of the mass estimation calculation unit. Figure 7 is a flowchart showing the processing contents of the calculation permission determination unit. Figure 8 is a control block diagram showing the processing contents of the acceleration sensor correction unit. Figure 9 is a control block diagram showing the processing contents of the vehicle body pitch angle estimation unit. Figure 10 is a control block diagram showing the processing contents of the gradient angle estimation unit. Figure 11 is a time chart when no correction is made to the longitudinal acceleration sensor values. Figure 12 is a time chart when correction is made to the longitudinal acceleration sensor values. Figure 13 is a list of vehicle parameters related to pitching.

[0009] Embodiments of the present invention will be described below with reference to the drawings.

[0010] [Configuration of Vehicle 100] Figure 1 is a block diagram illustrating the configuration of vehicle 100 to which the control system for electric vehicles of this embodiment is applied. Vehicle 100 is an electric vehicle. An electric vehicle is a vehicle that is equipped with a drive motor (hereinafter simply referred to as motor 4) as a drive source and runs by generating a driving force caused by the torque generated by motor 4 in one or more wheels. For this reason, electric vehicles include not only so-called electric vehicles but also hybrid vehicles that use both motor 4 and an engine as a drive source. For example, electric vehicles also include hybrid vehicles that use motor 4 as a drive source for either the front wheels or the rear wheels and an engine as a drive source for the other wheel. Furthermore, a four-wheel drive vehicle is a vehicle that uses four wheels as drive wheels 9. A four-wheel drive vehicle includes not only vehicles that always use four wheels as drive wheels 9 but also vehicles that can switch between so-called front-wheel drive or rear-wheel drive (two-wheel drive) and four-wheel drive. Furthermore, a four-wheel drive vehicle can control some of its four wheels in conjunction as drive wheels 9, or it may control the four wheels as independently driven drive wheels 9. Therefore, in this embodiment, an electric four-wheel drive vehicle refers to a vehicle 100 that moves by generating a driving force in some or all of its four wheels, which is caused by the torque generated by the motor 4.

[0011] As shown in Figure 1, the vehicle 100 is an electric four-wheel drive vehicle, but it may also be an electric two-wheel drive with only the front wheels or an electric two-wheel drive with only the rear wheels. The vehicle 100 comprises a front drive system fds, a rear drive system rds, a battery 1, and a motor controller 2 (acceleration estimation unit, error calculation unit, vehicle model correction unit, vehicle mass estimation unit, pitch angle acquisition unit).

[0012] The front drive system fds receives power from the battery 1 and drives the front wheels 9f under the control of the motor controller 2. The front drive system fds includes a front inverter 3f, a front drive motor 4f, a front reduction gear 5f, a front rotation sensor 6f, a front drive shaft 8f, and front wheels 9f. The subscript f indicates that it is a front-side component. The front wheels 9f are a pair of wheels that are relatively in the forward direction of the vehicle 100 out of the four wheels that the vehicle 100 has. The forward direction of the vehicle 100 is a predetermined direction formally determined according to the orientation of the driver's seat, etc. With the front drive system fds, the front wheels 9f function as drive wheels 9 that generate the driving force of the vehicle 100.

[0013] The rear drive system (rds) receives power from the battery (1) and drives the rear wheels (9r) under the control of the motor controller (2). The rear drive system (rds), symmetrically to the front drive system (fds), comprises a rear inverter (3r), a rear drive motor (4r), a rear reduction gear (5r), a rear rotation sensor (6r), a rear drive shaft (8r), and rear wheels (9r). The subscript 'r' indicates that it is a rear component. The rear wheels (9r) are the pair of wheels located relatively towards the rear of the vehicle (100) out of the four wheels on the vehicle (100). The rear direction of the vehicle (100) is the direction opposite to the forward direction of the vehicle (100). With the rear drive system (rds), the rear wheels (9r) function as drive wheels (9) that generate the driving force for the vehicle (100).

[0014] Battery 1 is connected to motor 4 via inverter 3 and supplies driving power to motor 4 by discharging. Battery 1 can also be charged by receiving regenerative power from motor 4. In the front drive system fds, battery 1 is connected to front drive motor 4f via front inverter 3f. Similarly, in the rear drive system rds, battery 1 is connected to rear drive motor 4r via rear inverter 3r.

[0015] The motor controller 2 is a control device for the vehicle 100 and is a computer composed of a central processing unit (CPU), read-only memory (ROM), random access memory (RAM), input / output interface (I / O interface), etc. The motor controller 2 generates control signals for controlling the front drive motor 4f and the rear drive motor 4r based on the vehicle variables of the vehicle 100. Vehicle variables are information that indicates the operating state or control state of the vehicle 100 as a whole or each part that constitutes the vehicle 100, and can be obtained by detection, measurement, or calculation, etc. Vehicle variables include, for example, the accelerator opening APO, longitudinal acceleration and lateral acceleration, vehicle speed V, gradient value, steering angle, wheel speed, as well as the rotational speeds Nmf and Nmr of each motor 4f and 4r, and the three-phase AC current, etc. The motor controller 2 uses these vehicle variables to control the front drive motor 4f and the rear drive motor 4r, respectively.

[0016] The front inverter 3f and rear inverter 3r convert the DC current supplied from the battery 1 into AC current by switching their switching elements on and off in response to the drive signal generated by the motor controller 2, and adjust the current supplied to the front drive motor 4f and rear drive motor 4r, respectively. In addition, each inverter 3f and 3r reverse-converts the AC current generated by the front drive motor 4f and rear drive motor 4r by regenerative braking force back into DC current, and adjusts the current supplied to the battery 1.

[0017] The front drive motor 4f and rear drive motor 4r are, for example, three-phase AC motors, and generate driving force (torque T) by AC current supplied from the connected inverter 3. The driving force generated by the front drive motor 4f is transmitted to the front wheels 9f via the front reduction gear 5f and front drive shaft 8f. Similarly, the driving force generated by the rear drive motor 4r is transmitted to the rear wheels 9r via the rear reduction gear 5r and rear drive shaft 8r. When the front drive motor 4f and rear drive motor 4r rotate together with the front wheels 9f and rear wheels 9r, respectively, they generate regenerative braking force and recover the kinetic energy of the vehicle 100 as electrical energy. The front drive motor 4f constitutes a drive source (front drive source) that drives the front wheels 9f. Similarly, the rear drive motor 4r constitutes a drive source (rear drive source) that drives the rear wheels 9r independently of the front wheels 9f.

[0018] The front reduction gear 5f and the rear reduction gear 5r are composed of, for example, multiple gears. Each of these reduction gears 5f and 5r reduces the rotational speed Nm of the motor 4 to which it is connected and transmits it to the drive shaft 8, thereby generating a drive torque or braking torque proportional to the reduction ratio. The front rotation sensor 6f and the rear rotation sensor 6r detect the rotor phase α of the motor 4 to which they are connected and output it to the motor controller 2. The motor controller 2 detects the rotational speed Nmf of the front drive motor 4f based on the output of the front rotation sensor 6f, and detects the rotational speed Nmr of the rear drive motor 4r based on the output of the rear rotation sensor 6r. The front current sensor 7f and the rear current sensor 7r detect the current flowing through the motor 4 to which they are connected and output it to the motor controller 2. In this embodiment, these current sensors 7f and 7r detect the three-phase AC current of each motor 4f and 4r, respectively.

[0019] Vehicle 100 is equipped with various sensors 15 in addition to the front rotation sensor 6f and front current sensor 7f, rear rotation sensor 6r and rear current sensor 7r described above. The various sensors 15 include, for example, an accelerator opening sensor 15a, an acceleration sensor 15b, a vehicle speed sensor 15c, as well as a steering angle sensor, a wheel speed sensor, a brake fluid pressure sensor, etc. The accelerator opening sensor 15a detects the accelerator opening APO, which is the amount of accelerator operation. The acceleration sensor 15b detects the longitudinal and lateral acceleration of vehicle 100, that is, longitudinal acceleration and lateral acceleration. The vehicle speed sensor 15c detects the vehicle speed V of vehicle 100. The vehicle speed V is the speed of the entire vehicle body of vehicle 100, that is, the vehicle speed. The steering angle sensor detects the steering angle of the steering wheel. The wheel speed sensor detects the wheel speed of each drive wheel 9. The brake fluid pressure sensor detects the brake fluid pressure of the friction brake system. The detected values ​​from the various sensors 15 are input to the motor controller 2. The detection values ​​from the various sensors 15 may be input to other controllers such as the vehicle controller, and then input to the motor controller 2 via communication from those controllers.

[0020] In vehicle 100, the target torque T is the torque requested by the driver. ｍ ＊ This is distributed to the front wheel 9f and the rear wheel 9r. Therefore, the front torque distribution value T is the torque distribution value for the front wheel 9f. ｍf ＊ , and the rear torque distribution value T, which is the torque distribution value of the rear wheel 9r. ｍr ＊ Once one of them is determined, the other is also determined, and as a result, the torque distribution between the front and rear wheels (9f and 9r) is also determined.

[0021] [Control of Motor Controller 2] Next, the operation of the motor controller 2 will be explained with reference to Figure 2. Figure 2 is a flowchart of the control routine for drive force control that is executed by the motor controller 2. This control routine is executed repeatedly at predetermined intervals.

[0022] In step S201, the motor controller 2 performs input processing to acquire signals necessary for the control calculations described below through sensor input or communication with other controllers. The input signals are the current values ​​flowing through the front and rear motors 4, the rotor phase α and rotor angular velocity ω of the front and rear motors 4, the motor rotation speed Nm, the vehicle speed V, the accelerator opening θ, the DC voltage value Vdc, and the front and rear acceleration sensor values ​​a.

[0023] The current values ​​flowing through motor 4, i.e., the three-phase currents iu, iv, and iw, are obtained by the front current sensor 7f and the rear current sensor 7r. Since the sum of the three-phase current values ​​is zero, for example, iw may be calculated from the values ​​of iu and iv without being input to the sensor.

[0024] The rotor phase α [rad] of motor 4 is obtained by the front rotation sensor 6f and the rear rotation sensor 6r as described above.

[0025] The rotor angular velocity ω [rad / s] of motor 4 is obtained by differentiating the rotor phase α.

[0026] The motor rotation speed Nm [rpm] is obtained by dividing the rotor angular velocity ω by the number of pole pairs of motor 4 to obtain the motor rotation speed ωm [rad / s], which is the mechanical angular velocity of motor 4, and then multiplying it by 60 / 2π, which is the unit conversion coefficient from [rad / s] to [rpm].

[0027] The vehicle speed V [km / h] is obtained by the vehicle speed sensor 15c. The vehicle speed v [m / s] is calculated by multiplying the motor rotation speed ωm [rad / s] by the tire radius r and dividing by the final gear ratio, and then multiplying by the unit conversion coefficient from [m / s] to [km / h], which is 3600 / 1000. Alternatively, the vehicle speed V may be obtained via communication from a meter or another controller (e.g., a brake controller).

[0028] The accelerator opening angle θ [%] may be obtained by the accelerator opening angle sensor 15a, or by communication with the vehicle controller or other controllers.

[0029] The DC voltage value Vdc [V] may be obtained by a voltage sensor provided in the DC power line, or may be obtained by communication with the battery controller.

[0030] The front and rear acceleration sensor value a [m / s ２ is obtained by the acceleration sensor 15b.

[0031] In step S202, the motor controller 2 performs a basic target torque calculation process. In the basic target torque calculation process, based on the accelerator opening θ and the motor rotation speed ωm, the basic target torque T ｍ１ ＊ is set by referring to an accelerator opening-torque table. FIG. 3 is a diagram showing an example of an accelerator opening-torque table, where the vertical axis is the motor torque Tm [Nm] and the horizontal axis is the motor rotation speed ωm [rad / s]. The accelerator opening APO is divided into eight steps from fully closed to fully open, and the relationship between the motor rotation speed and the motor torque is set for each accelerator opening.

[0032] In step S203, the motor controller 2 performs a vibration suppression control process. In the vibration suppression control process, the basic target torque T ｍ１ ＊ and the motor rotation speed ωm are input, and the final target torque T ｍ２ ＊ that can suppress the vibration of the torque transmission system (for example, the torsional vibration of the drive shafts 8f and 8r, etc.) without sacrificing the response of the drive shaft torque is calculated.

[0033] In step S204, the motor controller 2 performs a vehicle mass estimation process. In the vehicle mass estimation process, the vehicle mass is estimated based on the final target torque T ｍ２ ＊ and the front and rear acceleration sensor value a. Details of the vehicle mass estimation process will be described later.

[0034] In step S205, the motor controller 2 performs a current command value calculation process. In the current command value calculation process, the current target values id*, iq* of the d-axis and q-axis are obtained by table reference from the final target torque T ｍ２ ＊ , the motor rotation speed ωm, and the DC current value Vdc.

[0035] In step S206, the motor controller 2 performs current control. In current control, first, the inverter calculates the current values ​​id and iq for the d and q axes from the three-phase current values ​​iu, iv, and iw and the rotor phase α. Next, the voltage command values ​​vd and vq for the d and q axes are calculated from the deviation between the target current values ​​id* and iq* for the d and q axes and the current values ​​id and iq for the d and q axes. Non-interference control may also be added here. Then, the three-phase voltage command values ​​vu, vv, and vw are calculated from the voltage command values ​​vd and vq for the d and q axes and the rotor phase α. The PWM signals (on duty) tu[%], tv[%], and tw[%] are calculated from these three-phase voltage command values ​​vu, vv, and vw and the DC voltage Vdc.

[0036] By controlling the switching elements of the inverter using the PWM signal obtained as described above, the motor 4 can be driven with the desired torque specified by the torque command value.

[0037] In the control routine described above, for example, in step S203, the final target torque T ｍ２ ＊ The state variables of the vehicle model used in the calculation include the vehicle mass. Therefore, the higher the accuracy of the vehicle mass estimation in step S204, the more appropriate the final target torque T will be in subsequent calculations. ｍ２ ＊ It becomes possible to configure this setting.

[0038] [Vehicle Mass Estimation Process] First, the vehicle model in this embodiment will be described.

[0039] Equation (1) is the equation for the vehicle.

[0040]

[0041] However, a is the longitudinal acceleration sensor value, M is the vehicle mass, u is the driving force, and e is the acceleration error.

[0042] Since the acceleration sensor 15b is a sensor that can detect acceleration in the longitudinal direction occurring in the vehicle, the longitudinal acceleration sensor value a also includes the gravitational acceleration component due to the gradient of the road surface.

[0043] The acceleration error includes errors in the mounting of the acceleration sensor 15b and errors in the detected value caused by the tilt of the vehicle due to the load.

[0044] Now, by using equation (2) to transform equation (1), we obtain equation (3).

[0045]

[0046]

[0047] Then, discretizing equation (3) yields equation (4).

[0048]

[0049] The reciprocal of the vehicle mass M ｉｎｖ To estimate the acceleration error e, the state variable x is set to the reciprocal of the vehicle mass M, M. ｉｎｖ By setting the acceleration error e and the observed value y to the longitudinal acceleration sensor value a, the state equation and the observation equation become equations (5) and (6), respectively.

[0050]

[0051]

[0052] Furthermore, the mean is zero, and the variance is σ. ｗ ２ System noise w is normal white noise, and mean zero, variance σ ｖ ２ When the observed noise v, which is the normal white noise, is taken into account, equations (5) and (6) become equations (7) and (8), respectively.

[0053]

[0054]

[0055] However, x ｋ , w, H ｋ These are equations (9), (10), and (11), respectively.

[0056]

[0057]

[0058]

[0059] Next, the details of the vehicle mass estimation process performed in step S204 will be explained with reference to Figure 4. Figure 4 is a control block diagram showing the contents of the vehicle mass estimation process.

[0060] In the torque correction unit S401, the target torque T ｍ ＊ Front drive wheel speed ω ｗ-ｆ , rear drive wheel speed ω ｗ-ｒ , and total resistance F ｌｏａｄ Based on this, the driving force u, which is the input signal for the mass estimation calculation unit S402, is calculated. ｌｏａｄ This includes air resistance and rolling resistance, as well as sliding resistance of each part.

[0061] Here, the details of the torque correction unit S401 will be explained with reference to Figure 5.

[0062] Figure 5 is a control block diagram showing the processing details of the torque correction unit.

[0063] In step S501, the front drive wheel speed ω ｗ-ｆ Approximate the derivative of the acceleration ω of each front drive wheel. ｗ-ｆ Calculate.

[0064] In step S502, the acceleration ω of each front drive wheel ｗ-ｆ In contrast, front wheel inertia J ｗf Front motor and differential inertia J ｍｅ－ｆ , wheel radius R ａf By multiplying by the gains composed of the above, the driving force equivalent value of the front drive wheel inertia is calculated.

[0065] In steps S503 and S504, the rear drive wheel speed ω ｗ-r The same process as in steps S501 and S502 is performed on the rear drive wheel inertia to calculate the driving force equivalent value. However, the components of the gain are the rear wheel inertia J ｗr , rear motor and differential inertia J ｍｅ-r , wheel radius R ａr In this embodiment, Raf and Rar are considered equal, and unless there is a particular need to distinguish between them, R is used. ａ That can also happen.

[0066] In step S505, the driving force equivalent value of the front drive wheel inertia, which is the output of step S502, and the driving force equivalent value of the rear drive wheel inertia, which is the output of step S504, are added together to calculate the driving force equivalent value of the drive wheel inertia.

[0067] In step S506, a low-pass filter is applied to the total resistance F for phase adjustment. ｌｏａｄ This is calculated using equation (12) with vehicle speed V, and parameter A ０ A １ A ２ Use the design value or the value identified through experimentation.

[0068]

[0069] In step S507, the target torque T is the output from step S203. ｍ ＊ The front torque distribution value T is the distribution value for the front drive wheels. ｍｆ ＊ In contrast, a low-pass filter is applied for phase adjustment.

[0070] In step S508, the gain K is the efficiency of the front motor 4f and the front drive force transmission system. ｅｆ Multiply by .

[0071] In Step S509, the front gear ratio is N ａｌｆ and wheel radius R ａｆ By multiplying by the gains composed of these elements, the unit is converted to the dimension of the driving force.

[0072] In steps S510 to S512, the rear torque distribution value T ｍｒ ＊ For this, gain K ｅｒ Rear gear ratio N ａｌｒ and wheel radius R ａｒ Using this, the same processing as in steps S507 to S509 is performed.

[0073] In step S513, the output of step S509 and the output of step S512 are added together. Then, in step S514, the driving force u is calculated by subtracting the outputs of steps S505 and S506 from the output of step S513.

[0074] Furthermore, the time constants used in the filtering processes in steps S501, S503, S506, S507, and S510 are all set to the same value in order to align the phases.

[0075] Returning to the explanation of Figure 4.

[0076] The mass estimation calculation unit S402 estimates the vehicle mass and acceleration error defined by equation (1) based on the driving force u and the vehicle's longitudinal acceleration sensor value (after correction) a. The details of this estimation process will be explained with reference to Figure 6. Figure 6 is a control block diagram showing the processing contents of the mass estimation calculation unit S402.

[0077] In step S601, by performing the processes of equations (5) and (6), the prior estimate of the state variable x^ ｋ｜ｋ－１ Then, the estimated value a^ from the vehicle's longitudinal acceleration sensor is calculated.

[0078] In step S602, the estimated vehicle longitudinal acceleration sensor value a^ is subtracted from the vehicle longitudinal acceleration sensor value a (after correction).

[0079] In step S603, the output value from step S602 is given a gain K. Ｋ By multiplying by x^, the prior estimate of the state variable is obtained. ｋ｜ｋ－１ Calculate the correction amount to compensate for the gain K. Ｋ This can be obtained by sequentially performing equations (13) to (15) when using the Kalman filter algorithm.

[0080]

[0081]

[0082]

[0083] Here, P is the error covariance matrix, K Ｋ P is the Kalman gain, Q and R are the covariance matrices with respect to system noise and observation noise, respectively. Ｋ While the algorithm updates the values ​​of Q and R, these are set arbitrarily, taking into account the noise and errors present in the sensors used for input and observed values. Similarly, the initial value of P should be set considering the magnitude of the initial estimation error.

[0084] The covariance matrix is ​​a matrix of covariances between the elements of a vector. A larger covariance means that the error included during state transitions and observations is larger. In this embodiment, the autocovariance (the diagonal elements of the covariance matrix) is important among the covariances. This is because the reciprocal M of the acceleration error e (a state variable) and the vehicle mass M... ｉｎｖ This is because they are independent of each other. In other words, Q and R are of the following form:

[0085]

[0086]

[0087] q ｅ , q Ｍｉｎｖ ,r ａ These are the autocovariances of e, M, and a, respectively. These values ​​are estimated based on experiments and prior knowledge. For example, Q depends on the sampling rate, and R depends on the noise characteristics of the sensor.

[0088] Also, gain K Ｋ This can be obtained by sequentially performing equations (18) to (20) when using the successive least squares algorithm with a forgetting factor.

[0089]

[0090]

[0091]

[0092] In the above, λ is the forgetting coefficient.

[0093] In step S604, the prior estimate of the state variable x^, which is the output of step S601, is obtained. ｋ｜ｋ－１ By correcting this with the output value from step S603, the estimated value of the state variable x^ ｋ｜ｋ Calculate.

[0094] Here, the state variables are the acceleration error e and the reciprocal of the vehicle mass M, M. ｉｎｖ Therefore, an estimated value of the vehicle mass M can be calculated using equation (2).

[0095] In step S605, the estimated value of the state variable is x^ｋ｜ｋ The past values ​​are sampled, and the process returns to step S601.

[0096] Returning to the explanation of Figure 4.

[0097] Depending on the mass estimation calculation permission flag calculated in step S403 described later, the calculation process in step S402 is performed as follows.

[0098] - If operation is permitted (operation permission flag = HI), the processes in steps S601 to S605 are repeated sequentially, and the estimated value of the state variable x^ ｋ｜ｋ By updating the estimated value of the state variable x^ ｋ｜ｋ Calculate.

[0099] - If the operation is not permitted (operation permission flag = LO), the processing in steps S601 to S605 is not performed, and the error covariance matrix P and the estimated value of the state variable x^ ｋ｜ｋ It retains the previous value.

[0100] The calculation permission determination unit S403 determines the braking amount, steering angle, and target torque T. ｍ ＊ Based on this, a calculation permission flag is calculated to determine whether the mass estimation calculation unit S402 is permitted or not. Details of the processing in the calculation permission determination unit S403 will be explained with reference to Figure 7. Figure 7 is a flowchart showing the processing contents in the calculation permission determination unit S403.

[0101] In step S701, the target torque T ｍ ＊ The time constant τ １ We approximate the derivative and calculate the torque change rate.

[0102] In step S702, it is determined whether the absolute value of the torque change rate is greater than or equal to the torque change rate threshold. If the absolute value of the torque change rate is greater than or equal to the torque change rate threshold, it is determined that there is a torque change and the process in step S703 is executed. If the absolute value of the torque change rate is less than the torque change rate threshold, it is determined that there is no torque change and the process in step S706 is executed.

[0103] In step S703, it is determined whether the absolute value of the steering angle is greater than or equal to the steering angle threshold. If the absolute value of the steering angle is less than or equal to the steering angle threshold, it is determined that there is no steering and the process in step S704 is executed. If the absolute value of the steering angle is greater than the steering angle threshold, it is determined that there is steering and the process in step S706 is executed.

[0104] In step S704, it is determined whether the braking amount is less than or equal to the braking amount threshold. If the braking amount is less than or equal to the braking amount threshold, it is determined that no braking is occurring and the process in step S705 is executed. If the braking amount is greater than the braking amount threshold, it is determined that braking is occurring and the process in step S706 is executed.

[0105] In step S705, it is determined that the operation should be permitted, and the operation permission flag is set to HI.

[0106] In step S706, it is determined that the operation should not be permitted, and the operation permission flag is set to LO.

[0107] Furthermore, τ １ The torque change rate threshold, operating angle threshold, and braking amount threshold are set to specific values ​​based on experimental results, etc., taking into consideration the degree of influence on the mass estimate. In this embodiment, the braking amount refers to the total braking amount, including the braking amount by friction brakes and the braking amount by regenerative brakes.

[0108] In the acceleration sensor correction unit S404, the vehicle longitudinal acceleration sensor value a' and the target torque T are used. ｍ ＊ , front and rear motor rotation speed ω ｍ Based on this, the vehicle's longitudinal acceleration sensor value (after correction), a, which is the input signal to the mass estimation calculation unit S402, is calculated. Here, the details of the processing of the acceleration sensor correction unit S404 will be explained with reference to Figure 8. Figure 8 is a control block diagram showing the processing contents of the acceleration sensor correction unit S404.

[0109] In step S801, processing is performed to correct for the effects of vehicle body pitch motion and gradient angle. The corrected longitudinal acceleration sensor value a is calculated using equation (21).

[0110]

[0111] Vehicle body pitch angle θ ｐｉｔｃｈ uses the value estimated from the vehicle motion characteristics, and the gradient angle θ ｇｒａｄｅ uses the value estimated from the parameters correlated with the motor torque and the motor rotation speed.

[0112] In step S802, low-pass filter processing for phase adjustment is performed on the vehicle longitudinal acceleration sensor value a'. The time constant used in the filter processing of step S802 is set to the same value as the time constant used in the filter processing of steps S501, S503, S506, S507, and S510 for aligning the phases.

[0113] In the vehicle body pitch angle estimation unit S803, based on the target torque T ｍ ＊ calculates the vehicle body pitch angle θ ｐｉｔｃｈ which is the input of the vehicle longitudinal acceleration sensor correction unit S801. The details of the processing here will be described with reference to FIG. 9. FIG. 9 is a control block diagram showing the processing content of the vehicle body pitch angle estimation unit S803.

[0114] Step S901 shows the estimation method of the vehicle body pitch angle θ ｐｉｔｃｈ First, the front torque distribution value T ｍ ＊ which is the distribution value of the target torque T ｍｆ ＊ to the front and rear motors 4f, 4r, and the rear torque distribution value T ｍｒ ＊ are each multiplied by the gain composed of the gear ratios N ａｌｆ of the front and rear gear mechanisms, N ａｌｒ and the wheel radii R ａｆ of the front and rear wheels, R ａｒ to convert the torque into the dimension of the driving force by unit conversion. The equation of motion from the driving forces F ｆ and F ｒ thus obtained to the vehicle body pitch angle θ ｐｉｔｃｈ will be described.

[0115] Assuming that the vehicle body above the spring is a rigid body, the inertial force, the driving force reaction force, and the vertical force due to the instantaneous rotation angle representing the operating state of the suspension act on the vehicle body above the spring during acceleration and deceleration, and the pitching moment M λ is represented by Equation (22).

[0116]

[0117] Note that the instantaneous rotation angle θ ｆ , θ ｒ This value is fixed, assuming that the change during the stroke is negligible. Therefore, the equation of motion around the center of rotation of the pitch is expressed by equation (23).

[0118]

[0119] However, Cλ and Kλ are as shown in equations (24) and (25).

[0120]

[0121]

[0122] Therefore, by performing a Laplace transform on equation (23), we can obtain the respective driving forces F of the front drive motor 4f and the rear drive motor 4r. ｆ F ｒ The transmission characteristics from the vehicle body pitch angle θ can be expressed by the response of a second-order system, as shown in equation (26).

[0123]

[0124]

[0125]

[0126]

[0127] The parameters are as shown in the table in Figure 13. The auxiliary symbol f indicates the front wheel, and r indicates the rear wheel.

[0128] In the gradient angle estimation unit S804, the target torque T of the rear motor 4r is calculated. ｍ-r ＊ and motor rotation speed ω ｍ-r The input is the gradient angle θ which becomes the input to the acceleration sensor calculation unit S801. ｇｒａｄｅ The following is calculated. Details of this calculation will be explained with reference to Figure 10. Figure 10 is a control block diagram showing the processing contents of the gradient angle estimation unit S804.

[0129] In step S1001, the target torque T ｍ-r＊ and motor rotation speed ω ｍ-r Model G of the transfer characteristics ｐ H(s) / G is obtained using a low-pass filter H(s) whose order is greater than or equal to the difference between the numerator and denominator orders of (s). ｐ Using (s), the motor rotation speed ω ｍ-r The data is filtered to calculate the first estimated motor torque.

[0130] In step S1002, a low-pass filter H(s) is used to target the torque T ｍ-r ＊ The data is filtered to calculate a second estimated motor torque.

[0131] Then, the difference T between the first motor torque estimate and the second motor torque estimate. ｄ (Hereafter, this will also be referred to as the disturbance torque estimate.) is calculated.

[0132] The disturbance torque estimate T calculated in this way ｄ And, gear ratio N ａｌｒ and wheel radius R ａｒ The gain is composed of the above, and the gradient angle θ is calculated using equation (30). ｇｒａｄｅ Calculate.

[0133] In this embodiment, since the vehicle 100 is a four-wheel drive vehicle, the target torque T of the front motor 4f ｍ-f ＊ and motor rotation speed ω ｍ-f By performing the same process with the input θ, the gradient angle θ can also be obtained. ｇｒａｄｅ It is possible to estimate this.

[0134] Furthermore, in this embodiment, the gradient angle θ is obtained by the above calculation. ｇｒａｄｅ This is estimated, but it may also be detected using a gradient sensor or similar device.

[0135] [Effects] The effects of implementing the above control will be explained with reference to Figures 11 and 12. Figure 11 is a time chart when no correction is made to the longitudinal acceleration sensor values ​​(hereinafter also referred to as the comparative example). Figure 12 is a time chart when the control of this embodiment is applied, that is, when correction is made to the longitudinal acceleration sensor values. In both Figures 11 and 12, the solid line in the vehicle mass chart shows the estimated value, and the dashed line shows the true value. Note that both Figures 11 and 12 were obtained by simulation. In reality, the vehicle mass changes to an extent that affects the control when the number of passengers increases or decreases or when cargo is loaded or unloaded, that is, when the vehicle stops, but in the above simulation, the vehicle mass is assumed to change while driving.

[0136] First, let's explain Figure 11 as a comparative example.

[0137] The vehicle mass estimation calculation begins at timing T0, when the vehicle is traveling at a constant speed on a flat road. Since the vehicle's pitch motion affects the acceleration sensor values, an error occurs in the estimated vehicle mass.

[0138] At timing T1, when the road surface changes from a flat road to an uphill road, the gradient angle also affects the acceleration sensor value, resulting in a change in longitudinal acceleration.

[0139] When the vehicle mass (true value) changes at timing T2, errors occur in the acceleration sensor value due to the effects of the vehicle's pitch motion and gradient angle, and consequently, errors also occur in the estimated value of the vehicle mass. As a result of these errors, a discrepancy remains between the estimated value and the true value even as time passes.

[0140] Next, Figure 12 will be explained.

[0141] The conditions are the same as in Figure 11: the calculation starts at timing T0 when the vehicle is traveling at a constant speed on a flat road, the gradient changes from a flat road to an uphill road at timing T1, and the vehicle mass (true value) changes at timing T2.

[0142] In this embodiment, the acceleration sensor value is corrected based on the vehicle body pitch angle, so the vehicle mass can be estimated without error from timing T0 to timing T1.

[0143] Furthermore, in this embodiment, the acceleration sensor value is also corrected based on the gradient angle, so the vehicle mass can be estimated without error even after the timing T1 when the road changes to an incline.

[0144] Then, when the vehicle mass (true value) changes at timing T2, the estimated value deviates from the true value immediately after the change, but converges to the true value over time.

[0145] As described above, errors occur in the acceleration sensor values ​​due to the effects of vehicle pitch motion and gradient angle. Estimating the vehicle mass with these errors present leads to a decrease in estimation accuracy. In this embodiment, the acceleration sensor values ​​are corrected to take these effects into account, and the vehicle mass is estimated based on the corrected values, thereby improving estimation accuracy.

[0146] In this embodiment, the use of estimated vehicle mass for current control was described as an example, but estimated vehicle mass can also be used for other types of control. For example, it can be used for braking force control to maintain an appropriate distance between vehicles and avoid collisions in vehicles equipped with driver assistance systems, and for estimating the remaining driving range in electric vehicles, etc.

[0147] As described above, this embodiment provides a vehicle mass estimation method that calculates an estimated acceleration, which is an estimated value of the longitudinal acceleration of the vehicle 100, based on the driving force generated by the motor (power source) 4 for driving the vehicle 100 and a predetermined vehicle model, calculates the error between the estimated acceleration and the actual acceleration, which is the longitudinal acceleration of the vehicle 100 detected by the acceleration sensor (longitudinal acceleration sensor) 15b, corrects the vehicle model according to the calculated error, and estimates the mass of the vehicle based on the corrected vehicle model. In this method, the vehicle body pitch angle θ is obtained, the actual acceleration is corrected according to the vehicle body pitch angle θ, and the error between the corrected actual acceleration and the estimated acceleration is calculated. If vehicle body pitch motion occurs due to acceleration or deceleration of the vehicle 100, an error may occur between the sensor value of the acceleration sensor 15b and the actual longitudinal acceleration of the vehicle, which may reduce the accuracy of the vehicle mass estimation. However, according to this embodiment, the above error is suppressed by applying a correction to the sensor value of the acceleration sensor 15b that takes into account the effect of vehicle body pitch motion, as described above, so that the accuracy of the vehicle mass estimation can be improved.

[0148] According to this embodiment, the vehicle body pitch angle θ is obtained by detection or estimation calculation, the value obtained by multiplying the gravitational acceleration by sinθ is subtracted from the actual acceleration, and the value after subtraction is divided by cosθ to obtain the corrected actual acceleration. This makes it possible to correct the sensor value of the acceleration sensor 15b by a simple calculation using the vehicle body pitch angle and calculate the correct longitudinal acceleration with respect to the direction of travel of the vehicle body.

[0149] In this embodiment, the driving force is used as input, and the vehicle body pitch angle θ is estimated based on the dynamic characteristics on the spring. This makes it possible to estimate the vehicle body pitch angle θ without adding a sensor to detect the vehicle body pitch angle θ.

[0150] In this embodiment, the gradient angle of the road surface on which the vehicle 100 is traveling is detected or estimated, the orthogonal component of the gravitational acceleration with respect to the road surface is calculated using the gradient angle, the value obtained by multiplying the orthogonal component by sinθ is subtracted from the actual acceleration, and the value after subtraction is divided by cosθ to obtain the corrected actual acceleration. By correcting the sensor value of the acceleration sensor 15b in this way, taking into account the effect of the road surface gradient angle, it becomes possible to estimate the vehicle mass with higher accuracy.

[0151] In this embodiment, the gradient angle is estimated based on parameters correlated with the driving force and the rotational speed of the motor 4. This makes it possible to estimate the gradient angle without adding a sensor to detect the gradient angle.

Claims

Based on the driving force generated by the power source for driving the vehicle and a predetermined vehicle model, the estimated acceleration, which is an estimated value of the vehicle's longitudinal acceleration, is calculated. The error between the estimated acceleration and the actual acceleration, which is the longitudinal acceleration of the vehicle detected by the acceleration sensor, is calculated. The vehicle model is corrected according to the calculated error. In a vehicle mass estimation method that estimates the mass of a vehicle based on the corrected vehicle model, Obtain the vehicle body pitch angle θ, A method for estimating vehicle mass, comprising correcting the actual acceleration according to the vehicle body pitch angle θ, and calculating the error between the corrected actual acceleration and the estimated acceleration. 　 In the vehicle mass estimation method described in claim 1, The vehicle body pitch angle θ is obtained by detection or estimation calculation, A method for estimating vehicle mass, comprising subtracting the value obtained by multiplying the acceleration due to gravity by sinθ from the actual acceleration, and then dividing the subtracted value by cosθ to obtain the corrected actual acceleration. 　 In the vehicle mass estimation method described in claim 2, A method for estimating vehicle mass, which uses the aforementioned driving force as input and estimates the vehicle body pitch angle θ based on the dynamic characteristics on the spring. 　 In the vehicle mass estimation method described in claim 2, The gradient angle of the road surface on which the vehicle is traveling is detected or estimated by calculation, Using the aforementioned gradient angle, the orthogonal component of the gravitational acceleration with respect to the road surface is calculated. A method for estimating vehicle mass, comprising subtracting the value obtained by multiplying the orthogonal component by sinθ from the actual acceleration, and dividing the subtracted value by cosθ to obtain the corrected actual acceleration. 　 In the vehicle mass estimation method described in claim 4, A method for estimating vehicle mass, which estimates the gradient angle based on parameters correlated with the driving force and the rotational speed of the drive source. 　 An acceleration estimation unit calculates an estimated acceleration, which is an estimated value of the longitudinal acceleration of a vehicle, based on the driving force generated by a power source for driving the vehicle and a predetermined vehicle model. An error calculation unit calculates the error between the estimated acceleration and the actual acceleration, which is the longitudinal acceleration of the vehicle detected by the acceleration sensor. A vehicle model correction unit corrects the vehicle model according to the calculated error, A vehicle mass estimation device comprising a vehicle mass estimation unit that estimates the mass of a vehicle based on the corrected vehicle model, The vehicle body pitch angle acquisition unit is further equipped with a unit that acquires the vehicle body pitch angle θ. The error calculation unit corrects the actual acceleration according to the vehicle body pitch angle θ, and calculates the error between the corrected actual acceleration and the estimated acceleration, in this vehicle mass estimation device.

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