WO2019131310A1

WO2019131310A1 - Vehicle weight estimating device and vehicle weight estimating method

Info

Publication number: WO2019131310A1
Application number: PCT/JP2018/046489
Authority: WO
Inventors: 修一矢作
Original assignee: いすゞ自動車株式会社
Priority date: 2017-12-26
Filing date: 2018-12-18
Publication date: 2019-07-04
Also published as: CN111512126B; JP7095278B2; CN111512126A; JP2019117051A

Abstract

A vehicle weight estimating device 30 is configured such that: the vehicle weight estimating device is provided with a position sensor 24, rotation speed sensor 25, vehicle speed sensor 26, acceleration sensor 27, control unit 28, and vehicle weight calculation unit 31; the vehicle weight calculation unit 31 has a parameter acquisition unit 32, estimating unit 33, and selection unit 34; and the selection unit 34 selects and outputs an estimate value mx (k) as an output value mx in the cases where an integrated value ∑mx (k) deviates from an error range, and selects and outputs a previous output value mz as the output value mx in the cases where the integrated value ∑mx (k) is within the error range.

Description

Vehicle weight estimation device and vehicle weight estimation method

The present disclosure relates to a vehicle weight estimation device and a vehicle weight estimation method, and more particularly to a vehicle weight estimation device and a vehicle weight estimation method for estimating the weight of a vehicle with high accuracy.

There has been proposed an apparatus for correcting the value obtained by smoothing the estimated vehicle weight so as to fall within the predetermined range if the value is out of the preset range (see, for example, Patent Document 1). This device estimates the weight of the vehicle by using an upper limit value based on the maximum vehicle weight value and a lower limit value based on the minimum vehicle weight value as a range.

Japanese Patent Application Laid-Open No. 2004-301576

By the way, the estimated weight of the vehicle is used for control relating to the traveling of the vehicle. Therefore, an error due to the influence of noise or the like occurs in the parameters used for estimation, and the control related to the traveling of the vehicle also changes whenever the estimated weight of the vehicle changes. As such a change in control, there is exemplified a change in timing at which the shift position of the transmission is changed. This change in control gives the driver a sense of discomfort and is a factor that reduces drivability (drivability).

That is, in the device of the above example, even if the actual weight of the vehicle does not change, it is updated to the estimated weight of the vehicle, so the frequency of changes in control related to the traveling of the vehicle may increase There is a sex.

The present disclosure has been made in view of the above, and its object is to provide a vehicle weight estimation device and a vehicle weight estimation method for estimating the weight of a vehicle with high accuracy in accordance with the timing at which the weight of the vehicle changes. It is to provide.

A vehicle weight estimation apparatus according to an aspect of the present disclosure that achieves the above object comprises: parameter acquisition means for acquiring a parameter that changes during traveling of the vehicle; and the weight of the vehicle based on the parameter when the parameter is input. The estimation means for outputting the estimated value of the above, and the selection means for receiving the estimated value, wherein the selection means is configured such that the difference between the estimated value and the preset reference value is out of a predetermined range. An output value corresponding to the estimated value, and when the difference falls within the predetermined range, a previous output which is an output value output from the selecting means before estimating the estimated value A value is selected and configured to output either the selected output value or the previous output value.

A vehicle weight estimation method according to an aspect of the present disclosure for achieving the above object obtains a parameter that changes while the vehicle is traveling, estimates an estimated value as the weight of the vehicle based on the parameter, and estimates the estimated value. The difference between the estimated value and a preset reference value is calculated, it is determined whether or not the calculated difference is out of a predetermined range, and it is determined that the difference is out of the predetermined range. When an output value corresponding to the estimated value is selected as the weight, and it is determined that the difference falls within the predetermined range, the output value output as the weight of the vehicle prior to the estimation of the estimated value A certain previous output value is selected, and either the selected output value or the previous output value is output.

According to one aspect of the present disclosure, the weight of the vehicle can be estimated with high accuracy in accordance with the timing at which the weight of the vehicle has changed.

FIG. 1 is an explanatory view illustrating a first embodiment of a vehicle weight estimation device. FIG. 2 is a block diagram illustrating the control device of FIG. FIG. 3 is a part of a block diagram illustrating the vehicle weight calculator of FIG. FIG. 4 is a part of a block diagram illustrating the vehicle weight calculator of FIG. FIG. 5 is a flow diagram illustrating a first embodiment of a vehicle weight estimation method. FIG. 6 is a relationship diagram illustrating the relationship between the engine rotational speed and the fuel injection amount, and the engine torque.

Hereinafter, embodiments of a vehicle weight estimation apparatus and a vehicle weight estimation method will be described.

The vehicle weight estimation device 30 of the embodiment illustrated in FIGS. 1 to 4 is a device that is mounted on the vehicle 10 and estimates the weight of the vehicle 10 based on parameters that change while the vehicle 10 is traveling. Hereinafter, symbols with x and y appended to the code are variables, and indicate detected values or estimated values such as sensors, and those with k appended to the symbol indicate time series, and this k is “1 Increase one by one.

As illustrated in FIG. 1, in a vehicle 10 on which a vehicle weight estimation device 30 is mounted, a cab (cab) 12 is disposed on the front side of a chassis 11 and a body 13 is disposed on the rear side of the chassis 11.

An engine 14, a clutch 15, a transmission 16, a propeller shaft 17, and a differential gear 18 are installed in the chassis 11. The rotational power of the engine 14 is transmitted to the transmission 16 via the clutch 15. The rotational power shifted by the transmission 16 is transmitted to the differential gear 18 through the propeller shaft 17 and is distributed as a driving force to the pair of drive wheels 19 which are rear wheels. A torque converter may be interposed between the engine 14 and the clutch 15.

The control device 20 is electrically connected to the engine 14, the clutch 15, the transmission 16, and various sensors via signal lines indicated by alternate long and short dashed lines. As various sensors, an accelerator opening sensor 22 for detecting the accelerator opening Ax from the depression amount of the accelerator pedal 21 and a position sensor 24 for detecting the lever position Px of the shift lever 23 are installed in the cab 12. The chassis 11 is provided with a rotational speed sensor 25 for detecting the rotational speed Nx of a crankshaft (not shown) of the engine 14, a vehicle speed sensor 26, and an acceleration sensor 27.

The control device 20 is hardware including a CPU that performs various information processing, an internal storage device that can read and write programs used to perform the various information processing, and information processing results, and various interfaces.

As illustrated in FIG. 2, the control device 20 includes, as functional elements, a control unit 28 that controls the engine 14, the clutch 15, and the transmission 16, and a vehicle weight calculation unit 31 that calculates the weight of the vehicle 10. . In this embodiment, each functional element is stored as a program in the internal storage device, but each functional element may be configured by individual hardware.

The vehicle weight estimation device 30 includes a position sensor 24, a rotational speed sensor 25, a vehicle speed sensor 26, an acceleration sensor 27, a control unit 28, and a vehicle weight calculation unit 31. The vehicle weight calculation unit 31 functions as a parameter acquisition unit, an estimation unit, and a selection unit, receives the detection values of those sensors and the calculation result of the calculation unit, and calculates the result based on each detection value and calculation result Is output as the output value mx.

The control unit 28 is a functional element that functions as a part of the parameter acquisition unit, and in this embodiment acquires the fuel injection amount Qx in the engine 14 at each sampling cycle ts. The fuel injection amount Qx is proportional to the injection time (drive pulse) of an injector (not shown) of the engine 14 and is obtained from the total value of the injection times.

The control unit 28 receives the accelerator opening degree Ax detected by the accelerator opening degree sensor 22 and calculates a reference injection time based on the accelerator opening degree Ax. Next, the control unit 28 is added based on the presence or absence of driving of the on-vehicle device mounted on the vehicle 10 and driven by the engine 14 and the presence or absence of regeneration of the exhaust gas purification device purifying the exhaust gas discharged from the engine 14 Calculate the injection time. When the fuel injection amount based on the additional injection time is injected, the driving force of the in-vehicle device is compensated, and the exhaust gas purification device is regenerated. Next, the control unit 28 calculates the fuel injection amount Qx based on the sum of the reference injection time and the additional injection time for each sampling cycle ts.

The control unit 28 is not limited to this configuration as long as the fuel injection amount Qx actually injected in the engine 14 can be obtained. The control unit 28 may calculate the reference injection time from the internal pressure of the intake manifold (not shown), the volumetric efficiency, and the required air-fuel ratio, or from the intake air amount and the engine rotational speed Nx. As an on-vehicle device, an air compressor, a motor generator, etc. can be illustrated. As an exhaust gas purification apparatus, the collection filter which collects the particulate matter in exhaust gas can be illustrated.

The position sensor 24 is a device that functions as a part of parameter acquisition means, and detects the lever position Px required by the driver by electrically detecting the position of the shift lever 23 operated by the driver of the vehicle 10 Do. The position sensor 24 detects the gear ratio ix of the transmission 16 according to the lever position Px for each sampling cycle ts. As the lever position Px, a parking position (P position), a reverse position (R position), a neutral position (N position), a forward position (D range) and the like can be exemplified. For example, a plurality of first to sixth speeds is set as the forward position. A gear ratio ix is set to each forward position, which decreases as the number of stages increases from the first speed. When the transmission 16 is configured by an AMT, instead of the position sensor 24, one having a function of reading the gear position of the transmission 16 controlled by the control unit 28 may be used. When the gear ratio ix of the transmission 16 is obtained from the control signal of the control unit 28, the gear ratio ix can also be obtained based on the vehicle speed vx and the engine rotation speed Nx.

The vehicle speed sensor 26 is a device that functions as a part of parameter acquisition means, reads a pulse signal proportional to the rotational speed of the propeller shaft 17, and the vehicle speed vx for each sampling cycle ts by vehicle speed calculation processing (not shown) of the control device 20. It is a sensor to acquire. Since the vehicle speed sensor 26 acquires the vehicle speed vx based on a pulse signal proportional to the rotational speed, the acquired vehicle speed vx is not negative but has a value of zero or more. As the vehicle speed sensor 26, a sensor for acquiring the vehicle speed vx from the rotational speed of the output shaft (not shown) of the transmission 16, the drive wheel 19, the driven wheel, etc. may be used. In addition, when using the sensor which acquires the vehicle speed vx from rotational speeds, such as a driving wheel 19 and a driven wheel, it is good to acquire each rotational speed of a pair of right and left wheels, and to make the average value into the vehicle speed vx.

The acceleration sensor 27 is a device that functions as a part of the parameter acquisition unit, and operates by an acceleration component accompanying a speed change in the front-rear direction of the vehicle 10 and a gravity acceleration component accompanying a posture change of the vehicle 10. The acceleration sensor 27 is a sensor that acquires an acceleration component parallel to the road surface obtained by combining them, that is, an acceleration Gx in the front-rear direction of the vehicle 10, for each sampling cycle ts. Examples of the acceleration sensor 27 include a mechanical displacement measurement method, an optical method, and a semiconductor method.

As illustrated in FIGS. 3 and 4, in this embodiment, the vehicle weight calculation unit 31 includes a parameter acquisition unit 32, an estimation unit 33, and a selection unit 34 as each functional element. Although each functional element of the vehicle weight calculation unit 31 is stored in the internal storage device as a program, each functional element may be configured by individual hardware.

The parameter acquisition unit 32 functions as a parameter acquisition unit, and receives detection values of the control unit 28 and each sensor. The parameter acquisition unit 32 is a functional element that outputs, to the estimation unit 33, a first parameter xx and a second parameter yy as parameters that change while the vehicle 10 is traveling for each sampling cycle ts. The parameter acquisition unit 32 includes a first parameter calculation block 32a, a second parameter calculation block 32b, and an engine torque calculation block 32c.

The first parameter calculation block 32a is a functional element that receives the acceleration Gx and calculates a first parameter xx. The second parameter calculation block 32b is a functional element that receives the vehicle speed vx, the gear ratio ix of the transmission 16, and the engine torque Te to calculate a second parameter yy. The engine torque calculation block 32 c is a functional element that receives the engine rotation speed Nx and the fuel injection amount Qx and calculates an engine torque Te that is actually output from the engine 14.

The estimation unit 33 functions as an estimation means, and receives the first parameter xx and the second parameter yy, and combines them with the previous estimated value mx (k−1) estimated one before in the sampling period ts. It is a functional element that outputs an estimated value mx (k) estimated based on smoothing processing. The estimation unit 33 is configured of an RLS estimation block. The RLS estimation block updates the variables in the estimation operation every sampling period ts. That is, when a new parameter is input, the RLS estimation block estimates the previous estimated value mx (k-1), the covariance matrix P (k-1), and the gain K (k-1) calculated by the RLS algorithm. It is in the stored state.

The selection unit 34 functions as a selection unit, and the estimated value mx (k) output from the estimation unit 33 is sequentially input. The selection unit 34 is a functional element that selects and outputs either the estimated value mx (k) or the previous output value mz as the output value mx based on the difference between the estimated value mx (k) and the reference value ma. .

The difference between the estimated value mx (k) and the reference value ma is the integrated value mxmx of the temporal change from the reference value ma to the estimated value mx (k) until the estimated value mx (k) is input. k). That is, the selection unit 34 changes the variation Δmx (k), which is the difference between the input estimated value mx (k) and the previous estimated value mx (k−1), to the previous estimated value mx (k−1) and the reference value ma. Is a functional element that calculates an integrated value mx mx (k) integrated with the difference Δ mx (k-1) of

The reference value ma is a value that is updated at the timing when the estimated value mx (k) is output as the output value mx. As an initial value of the reference value ma, a reference vehicle weight W0 is exemplified. As the reference vehicle weight W0, a vehicle weight which is a weight of the vehicle 10 at the time of an empty vehicle, that is, a weight (including the engine 14 etc.) of the main body (chassis 11, cab 12 and body 13) of the vehicle 10 is exemplified. The vehicle weight may include the weight of fuel, oil, cooling water, spare tire, tools and the like. In addition, as the reference value ma, a total vehicle weight, that is, a weight obtained by adding the total weight of the maximum passenger capacity and the weight of the maximum load capacity to the vehicle weight is exemplified.

In this embodiment, the selection unit 34 includes a previous estimated value acquisition block (delay block) 34a, an addition block 34b, an integration block (also referred to as an integrator or integrator) 34c, an absolute value block 34d, a comparison block 34e, a switch block 34f, And a previous output value acquisition block (delay block) 34g.

The previous estimated value acquisition block 34a, the addition block 34b, and the integration block 34c are functional elements for calculating the difference between the input estimated value mx (k) and the reference value ma, and the integrated value mx mx (k) is used as the difference. It is a functional element to calculate. Specifically, the previous estimated value acquisition block 34a, the addition block 34b, and the integration block 34c change the difference between the estimated value mx (k) and the previous estimated value mx (k-1) every fixed period (sampling time). It is a functional element that calculates the amount Δmx (k) and calculates an integrated value mxmx (k) obtained by integrating the calculated change amount Δmx (k).

The change amount Δmx (k) is a difference between the acquired current estimated value mx (k) and the previously acquired previous estimated value mx (k−1). As the change amount Δmx (k), for example, a change amount per fixed period (sampling time) may be used. The amount of change Δmx (k) is positive (+) when increasing from the previous estimated value mx (k−1) to the estimated value mx (k), and negative (−) when decreasing. The integrated value mx mx (k) is the sum of the change amounts Δ mx (k) calculated for each fixed period (sampling time), and the change amount Δ mx (k) for each fixed period up to the present time after reset is sequentially Calculated by adding. For example, when reset in the previous cycle, the integrated value 変化 mx (k) becomes the change amount Δ mx (k), and when it has not been reset even once, the integrated value mx mx (k) changes the change amount Δ mx (1) to the change amount It is the sum of Δmx (k). The integration block 34 c resets the integration value Σ mx (k) to zero (“0”) when “1” which is a binary signal started from the comparison block 34 e is input. Resetting the integrated value Σ mx (k) substantially updates the reference value ma to the estimated value mx (k), that is, setting the estimated value mx (k) to the next reference value ma It is synonymous with

The absolute value block 34 d and the comparison block 34 e are functional elements that determine whether or not the integrated value mx mx (k) is out of the range of error (−Wa to + Wa). The comparison block 34 e transmits “1” (a signal indicating true) as a binary signal when the integrated value mx mx (k) deviates from the range of the error (| Σ W x |> Wa). On the other hand, when the integrated value mx mx (k) falls within the range of error (| Σ W x | a Wa), “0” (a signal indicating false) is transmitted as a binary signal. In the present specification, in the case where the integrated value mx mx (k) is a value of + Wa or -Wa, it is assumed to fall within the range of the error.

Next, the estimation operation of the estimated value mx (k) by the estimation unit 33 of this embodiment will be described. The estimation unit 33 estimates an estimated value mx using an adaptive algorithm as a smoothing process, regarding the motion equation in the front-rear direction of the vehicle 10 as a transfer function based on each parameter and the previous estimated value mx (k-1). Estimate (k). As an adaptation algorithm, RLS (Recursive Least Square) algorithm (sequential least squares algorithm) is used.

An equation of motion in the front-rear direction of the vehicle 10 is expressed by the following equation (1). In equation (1), vx 'is a differential value obtained by time-differentiating the vehicle speed vx, Tw is a drive torque transmitted to the drive wheel 19, rw is a wheel diameter of the drive wheel 19, and .DELTA. , B is a constant, g is a gravitational acceleration, and μ is a rolling resistance coefficient. The constant B is a constant multiplied by “0.5”, the air density ρ, the front projection area Af of the vehicle 10, and the air resistance coefficient Cd. The wheel diameter rw, the constant B, and the rolling resistance coefficient μ are obtained as values unique to the vehicle 10.

When the above equation (1) is modified, the weight mx of the vehicle 10 is expressed by the following equation (2).

The above equation (2) can be regarded as a transfer function with the first parameter xx as an input value, the second parameter yy as an output value, and the estimated value mx as a variable. Therefore, the transfer function (Φy (k) = Φx (k) · mx (k)) is self-adapted according to the RLS algorithm to estimate the estimated value mx (k). The estimated value mx (k) is expressed by the following equations (3) to (5). In the following equation, mx (k-1) is a previously estimated value which is an estimated value estimated one before in the sampling period ts, K (k) is a gain calculated by the RLS algorithm, and P (k) is The covariance matrix, I is an identity matrix, and " ^T " is a transposed matrix.

Once the initial value P (0) of the covariance matrix P (k) is determined, the covariance matrix P (k) is obtained based on the above equation (5) and the gain based on the equation (4) using the parameter xx. K (k) can be calculated respectively. That is, whenever the first parameter xx and the second parameter yy are newly obtained, the covariance matrix P (k) and the gain K (k) are newly updated. Then, the estimated value mx (k) can be calculated by a method of correcting the previous estimated value mx (k−1) estimated immediately before on the basis of these and the equation (3).

The initial value P (0) is represented by the product of the constant α and the unit matrix I. Although a value of about 1000 is usually used as the constant α, it is preferable to set the constant α small if noise is large. The constant α is determined by the magnitude of noise. Further, as the initial value m (0), for example, it is preferable to use the weight of the vehicle when the driver or the load is removed, the total weight of the vehicle at the maximum loading, or the average value of the estimated value mx (k).

As the covariance matrix P (k) increases, the estimated value mx (k) moves away from the true value, and when the covariance matrix P (k) converges to a smaller value, the estimated value mx (k) approaches the true value.

As described above, the estimated value mx (k) can be sequentially smoothed by estimating the estimated value mx (k) by the adaptive algorithm with the above equation (2) as the transfer function. This is advantageous for speeding up the convergence to the true value and improving the robustness against noise, disturbance, or a change in statistical properties of detected values of each sensor, and can reduce estimation errors. Along with this, the weight of the vehicle 10 can be estimated with high accuracy.

In this embodiment, by using the RLS algorithm of the adaptation algorithm, the estimated value mx (k) can be obtained by the above equations (3) to (5). This is advantageous for on-line estimation, and can calculate the estimated value mx (k) in real time. Further, as compared with the method of removing noise from the detection value acquired by each sensor by the low pass filter, it is advantageous for securing the responsiveness of the estimation of the weight of the vehicle 10.

In addition, the previous estimated value mx (k-1), the covariance matrix P (k-1), and the gain K (k-1) need only be updated for each sampling period ts, and the internal storage device of the control device 20 You can minimize the numbers to be stored. Therefore, storage required for estimation as compared with the method by offline estimation (batch processing estimation) in which an infinite storage area must be secured for the uncertain traveling period of the vehicle 10 in the internal storage device of the control device 20 It is advantageous to reduce the capacity. The off-line estimation mentioned here can be exemplified by a batch processing least squares method, a method of calculating an average value of all the estimated values mx (0) to mx (k), and the like.

Furthermore, by using the RLS algorithm, the estimated value mx (k) can be calculated for each sampling period ts. This is advantageous for estimation in real time as compared to a method of estimating when the state of the vehicle 10 (for example, the gear ratio ix or the driving torque Tw) changes or when traveling a predetermined distance.

Next, the vehicle weight estimation method will be described as each function of the vehicle weight calculation unit 31 with reference to the flowchart of FIG. 5. The following vehicle weight estimation method is started when the control device 20 of the vehicle 10 is energized, and is repeatedly performed for each sampling cycle ts to estimate the weight of the vehicle 10 in real time. That is, processing from start to return is performed in one sampling period ts. Then, when the control device 20 loses power, it ends.

If it starts, the vehicle weight calculation part 31 will acquire the parameter which changes during driving | running | working of the vehicle 10 by the function of the parameter acquisition part 32 (S110). The parameters are a first parameter xx and a second parameter yy.

Specifically, the parameter acquisition unit 32 acquires those parameters from the detection values detected by the control unit 28 and each sensor. First, fuel injection amount Qx by control unit 28, gear ratio ix of transmission 16 by position sensor 24, engine rotation speed Nx by rotation speed sensor 25, vehicle speed vx by vehicle speed sensor 26, acceleration Gx by acceleration sensor 27 Get each one.

Next, the first parameter calculation block 32a calculates a first parameter xx shown in the following equation (6) by each block.

The acceleration Gx is an acceleration component parallel to the road surface obtained by combining the acceleration component accompanying the speed change in the front-rear direction of the vehicle 10 and the gravity acceleration component accompanying the attitude change of the vehicle 10 as described above. That is, the acceleration Gx is a value obtained by adding the differential value vx ′ and the gravitational acceleration component g · sin β. Thus, equation (6) is synonymous with the numerator of equation (2) above.

As a variable of the first parameter xx, a gravity acceleration component based on the differential value vx 'of the vehicle speed vx and the road surface gradient on which the vehicle 10 is traveling, instead of the acceleration Gx, as shown in Equation (2) above. Alternatively, g · sin β may be used. In this case, instead of the acceleration sensor 27, it is preferable to use a slope sensor for acquiring the road surface gradient on which the vehicle speed sensor 26 and the vehicle 10 are traveling, or a functional element for calculating the road surface gradient.

Next, the engine torque calculation block 32c calculates the actual engine torque Te output from the engine 14 based on the fuel injection amount Qx and the engine rotational speed Nx.

As illustrated in FIG. 6, the engine torque Te output from the engine 14 has a positive relationship with each of the engine rotation speed Nx and the fuel injection amount Qx, and the engine rotation speed Nx is fast and the fuel injection amount Qx The larger the, the larger. The map data is obtained in advance by experiments and tests, and stored in the engine torque calculation block 32c which is a data block.

In this embodiment, the engine torque Te is calculated from the relationship between the engine rotation speed Nx and the fuel injection amount Qx, but the accelerator opening Ax acquired by the accelerator opening sensor 22 may be used instead of the fuel injection amount Qx , Other acquisition methods may be used.

Next, the second parameter calculation block 32b calculates the drive torque Tw transmitted to the drive wheel 19 using the following equation (7). In equation (7), if indicates the gear ratio of the differential gear 18 and η indicates the transmission efficiency which is different depending on the gear ratio. The driving torque Tw may be obtained using a torque sensor or may be obtained by another method.

Next, the second parameter calculation block 32 b calculates the rotation part equivalent mass Δmx by the look-up table block 32 d.

The rotating part equivalent mass Δmx is a value determined according to the gear ratio ix which is a variable. The look-up table block 32d is set with a plurality of rotating portion equivalent masses Δmx for each gear ratio ix, and selects one corresponding to the gear ratio ix. The rotation portion equivalent mass Δmx may be calculated from the relationship between the weight of the vehicle at the time of an empty vehicle, the gear ratio ix, and a predetermined coefficient.

Next, the second parameter calculation block 32b calculates a second parameter yy shown in the following equation (8) by each block.

In this embodiment, the second parameter yy is expressed by the above equation (8), but the friction torque Tf acting on the engine 14, the clutch 15, the transmission 16, the differential gear 18, etc. may be taken into consideration. In this case, a value obtained by subtracting the friction torque Tf from the drive torque Tw may be divided by the wheel diameter rw of the drive wheel 19. Considering the friction torque Tf is advantageous for improving the estimation accuracy.

As described above, when each parameter is acquired, the vehicle weight calculation unit 31 estimates the estimated value mx (k) by the above-described estimation method of the estimation unit 33 (S120).

Next, the vehicle weight calculation unit 31 causes the selection unit 34 to input the estimated value mx (k) and the previous estimated value mx (k), which is a value input immediately before the estimated value mx (k) is input. A change amount Δmx (k) which is a difference from -1) is calculated (S130). Specifically, in this step, the change amount Δmx (k) is calculated by the previous estimated value acquisition block 34 a and the addition block 34 b. The change amount Δmx (k) may be calculated as the change amount of the estimated value mx (k) per unit time. In addition, the previous estimated value mx (k-1) immediately after the control device 20 is energized may be an estimated value input immediately before the control device 20 is stopped, and the reference which is the initial value of the reference value ma described above It may be a vehicle weight W0.

Next, the vehicle weight calculation unit 31 causes the selection unit 34 to calculate the integrated value mxmx of the temporal change between the reference value ma until the estimated value mx (k) is input and the estimated value mx (k). k) is calculated (S140). Specifically, in this step, the amount of change calculated in step S130 to the previous integrated value に mx (k-1) which is the difference between the previous estimated value mx (k-1) and the reference value ma by the integration block 34c. The integrated value mx mx (k) is calculated by adding Δ mx (k). That is, when the previous integrated value mx mx (k-1) is zero (“0”), the integrated value mx mx (k) calculated in this step is the change amount Δ mx (k).

Next, the vehicle weight calculation unit 31 determines whether the integrated value mx mx (k) is out of the range of error (−Wa to + Wa) by the selection unit 34 (S150). In this step, when the selection unit 34 exceeds the numerical value Wa of the range of errors by the absolute value of the integrated value mx mx (k), the process proceeds to the step of outputting the temporary estimated value mx (k) as the output value mx. On the other hand, if the absolute value of the integrated value mx mx (k) is less than or equal to the numerical value Wa of the error range, the process proceeds to the step of maintaining the previous output value mz.

When the absolute value of the integrated value mx mx (k) exceeds the numerical value Wa of the range of the error, the vehicle weight calculation unit 31 selects the estimated value mx (k) by the selection unit 34 (S160). Next, the vehicle weight calculation unit 31 causes the selection unit 34 to reset the integrated value mx mx (k) (S 170). In this step, the reference value ma is substantially updated to the estimated value mx (k) by resetting the integrated value mxmx (k) to zero. Next, the vehicle weight calculation unit 31 outputs the estimated value mx (k) selected by the selection unit 34 as the output value mx (S180), and returns to the start.

On the other hand, when the absolute value of the integrated value mx mx (k) is less than or equal to the numerical value Wa of the error range, the vehicle weight calculation unit 31 selects the previous output value mz by the selection unit 34 (S190). Next, the vehicle weight calculation unit 31 outputs the previous output value mz selected by the selection unit 34 as the output value mx (S180), and returns to the start.

Specifically, in the selection unit 34, the comparison block 34e determines whether the absolute value of the integrated value 数値 mx (k) exceeds the numerical value Wa in the range of the error (S150). If the absolute value of the integrated value mx mx (k) exceeds the numerical value Wa of the error range, the switch block 34 f to which “1” which is a binary signal started from the comparison block 34 e is input estimates k) is selected (S160). Next, the integration value mx mx (k) is reset by the integration block 34 c to which “1” which is a binary signal started from the comparison block 34 e is input (S 170).

On the other hand, if the absolute value of the integrated value mx mx (k) is less than or equal to the numerical value Wa of the error range, the switch block 34 f selects the previous output value mz (S 190).

As described above, the vehicle weight calculation unit 31 estimates the time when the integrated value mx mx (k) deviates from the error range (−Wa to + Wa) as the timing when the weight of the vehicle changes, and is estimated at that time. The estimated value mx (k) is output as an output value mx. On the other hand, the vehicle weight calculation unit 31 regards the time when the integrated value mx mx (k) falls within the range of error (-Wa to + Wa) as the time when the weight of the vehicle does not change, and the previous output value at that time Maintain the mz output.

That is, the vehicle weight calculation unit 31 eliminates the error in the sensing, detects the timing at which the weight of the vehicle 10 has changed, and outputs the output value mx to suppress the frequency at which the weight of the vehicle 10 is updated. Is advantageous. In addition, even when the estimated value mx (k) gradually changes with a value falling within the range of error, the change of the weight of the vehicle 10 is missed by judging the change by the integrated value mxmx (k). It is advantageous to As described above, the vehicle weight calculation unit 31 can estimate the weight with high accuracy in accordance with the timing at which the weight of the vehicle 10 has changed, and therefore gives the driver a sense of discomfort caused by a change in control using the weight. Therefore, drivability can be improved.

For example, when the control using the weight of the vehicle 10 is the shift control of the transmission 16, when the weight of the vehicle 10 is updated, the shift timing of the transmission 16 changes with the update. Therefore, the vehicle weight calculation unit 31 according to the embodiment updates the output value mx when the weight of the vehicle 10 actually changes. Therefore, since the shift timing can be changed in accordance with the change in weight of the vehicle 10, the drivability can be improved without giving the driver a sense of discomfort due to the change in shift timing.

Further, when the integrated value mx mx (k) falls within the error range, that is, when the weight of the vehicle does not actually change, the vehicle weight calculation unit 31 maintains the output of the previous output value mz. It is advantageous to reduce the estimation error of the vehicle weight.

The vehicle weight calculation unit 31 uses the range of the error as the threshold value for the integrated value mx mx (k), but may use a range other than the range of the error as long as it can be determined that the weight of the vehicle has changed. . However, by using the range of the error, it is possible to eliminate the influence of the error due to the accuracy and sensitivity of each sensor and the error due to the vibration of the sensor caused by the vibration of the vehicle 10, thereby reducing the estimation error of the road surface gradient. It is advantageous to

In the embodiment described above, the configuration for calculating the integrated value mx mx (k) as the difference between the estimated value mx (k) and the reference value ma is exemplified, but the estimated value when the reference value ma is reset at each reset Alternatively, the difference between the estimated value mx (k) and the reference value ma may be calculated for each fixed period (sampling time) by updating to mx (k).

In this embodiment, an example using the RLS algorithm as the estimation calculation of the estimated value mx (k) has been described, but the estimation unit 33 only needs to estimate the weight of the vehicle 10, and the estimation calculation is not limited thereto. For example, instead of the RLS algorithm, an LMS (Least Mean Square) algorithm, an NLMS (Nomalized Least Mean Square) algorithm, or the like may be used as an adaptation algorithm. In addition, averaging processing may be performed to output an average value of all estimated values mx (0) to estimated values mx (k). The averaging process is a specific pattern of the smoothing process.

It is sufficient that the temporary estimated value mx (k) can be calculated by a simple method, and is not limited to the method using only the equation of motion in the front-rear direction of the vehicle 10 shown in the above equation (2). For example, when the vehicle 10 is equipped with an air suspension, a method based on a change in the vertical direction of the vehicle 10 may be used. Alternatively, a method may be used that is based on the torque input to the transmission before and after the shift and the amount of change in rotational speed output from the transmission. Alternatively, a value obtained by adding the weight of the vehicle at the time of an empty vehicle to a value obtained by a weight sensor such as a load cell may be set as the temporary estimated value Mx.

Moreover, although the vehicle weight estimation apparatus 30 demonstrated the example comprised from the vehicle weight calculating part 31 and each sensor etc. in embodiment mentioned already, this indication is not limited to this. For example, the vehicle weight estimation device 30 may be configured of one sensor that functions as a parameter acquisition unit and a temporary estimation unit, and hardware that functions as an estimation unit and a maintenance unit.

This application is based on the Japanese Patent Application (Japanese Patent Application No. 2017-249663) filed on Dec. 26, 2017, the contents of which are incorporated herein by reference.

The vehicle weight estimation device and the vehicle weight estimation method of the present disclosure are useful in that the weight of the vehicle can be estimated with high accuracy in accordance with the timing at which the weight of the vehicle has changed.

Reference Signs List 10 vehicle 24 position sensor 25 rotational speed sensor 26 vehicle speed sensor 27 acceleration sensor 28 control unit 30 vehicle weight estimation device 31 vehicle weight calculation unit 32 parameter acquisition unit 33 estimation unit 34 selection unit x x first parameter 第一 y second parameter mx (k) Estimated value mx (k-1) Previous estimated value mx Output value mz Previous output value ma Reference value Δ mx (k) Change amount mx mx (k) Difference between estimated value and reference value (accumulated value of change amount)

Claims

Parameter acquisition means for acquiring parameters that change while the vehicle is traveling;
Estimation means for receiving the parameter and outputting an estimate of the weight of the vehicle based on the parameter;
Selecting means for receiving the estimated value.
When the difference between the estimated value and a preset reference value deviates from a predetermined range, the selection means selects an output value according to the estimated value, and the difference falls within the predetermined range. And selecting the previous output value which is the output value output from the selection means before estimating the estimated value, and outputting either the selected output value or the previous output value. Vehicle weight estimation device configured.
The vehicle weight according to claim 1, wherein the selection means calculates a difference between the estimated value and the reference value as an integrated value of change from the reference value to the estimated value until the estimated value is input. Estimator.
The vehicle weight estimation device according to claim 2, wherein the selection means sets the integrated value to zero when determining that the integrated value deviates from the predetermined range.
The vehicle weight estimation device according to claim 1 or 2, wherein the selection means sets the estimated value to a next reference value when the difference between the estimated value and the reference value deviates from the predetermined range.
The estimating means estimates the estimated value within a predetermined error range;
The vehicle weight estimation device according to any one of claims 1 to 4, wherein the predetermined range is set to the range of the error.
6. The estimation method according to claim 1, wherein the estimation means estimates the estimated value using smoothing processing based on the input parameter and a previous estimated value which is an estimated value estimated before acquiring the parameter. The vehicle weight estimation device according to any one of the items.
The estimation means estimates the estimated value using an adaptive algorithm as the smoothing process, based on the parameter and the previous estimated value, regarding the equation of motion in the longitudinal direction of the vehicle as a transfer function. The vehicle weight estimation apparatus of claim 6.
Get parameters that change while the vehicle is traveling,
Estimating an estimated value as the weight of the vehicle based on the parameters;
Calculating a difference between the estimated value estimated and a preset reference value;
It is determined whether or not the calculated difference is out of a predetermined range,
When it is determined that the difference deviates from the predetermined range, an output value corresponding to the estimated value is selected as the weight of the vehicle,
When it is determined that the difference falls within the predetermined range, a previous output value that is an output value output as the weight of the vehicle is selected before estimating the estimated value,
A vehicle weight estimation method for outputting either the selected output value or the previous output value.