CN105007058A - Real-time filtering method suitable for multi-dimensional wheel force sensor - Google Patents
Real-time filtering method suitable for multi-dimensional wheel force sensor Download PDFInfo
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Abstract
The present invention discloses a real-time filtering method suitable for a multi-dimensional wheel force sensor. The method comprises: firstly, based on operating principles of the multi-dimensional wheel force sensor, the relationship between a load applied on the wheel and the output of the multi-dimensional wheel force sensor are analyzed and established; secondly, according to the relationship, a state function taking a plane cornering model as a system is introduced; and finally, the output of the multi-dimensional wheel force sensor is regarded as the observed quantity, a Gauss quadrature integral point kalman filter is used for directly gain filtered real wheel force signal. The method overcomes the problem that the multi-dimensional wheel force sensor is hard to build, and achieves real-time highly precise filtering of the multi-dimensional wheel force sensor.
Description
Technical field
The present invention relates to automobile observation and control technology field, particularly relate to a kind of Real-Time Filtering method being applicable to Multi-component WFT.
Background technology
Car test techniqes is the foundation of adjoint auto industry and gradually grows up, and is widely used in the engineering fields such as vehicle research and development, Performance Detection and actual road test.Motor racing is that the effect of ground and wheel produces, and therefore, in vehicle traveling process, the measuring technology of vehicle wheel forces is the key technology in Automobile Road Test System.Along with the needs for automotive type exploitation and quality evaluation, wheel force snesor also develops from one dimension to multidimensional.Multi-component WFT can be directly used in the research of the collection, suspension performance, vehicle chassis control system etc. of road spectrum.Can not estimate because vehicle wheel forces signal has, non-linear and time the feature such as change, the data processing difficulty therefore for it is larger.China is weaker in this field, and to the data filtering of Multi-component WFT, especially the research of Real-Time Filtering aspect is in starting and exploratory stage substantially.
The object that patent of the present invention is applied is Multi-component WFT (the automobile wheel multi-dimensional force measuring device ZL200320110714.5 of Southeast China University's instrumental science and engineering college's independent research; Automobile wheel multi-dimensional force measuring sensor ZL200320110713.0), this Multi-component WFT can in perception vehicle travel process in the face of the active force of wheel, the semaphore that tractive effort wherein and normal pressure are paid close attention to for patent of the present invention.Tractive effort reflects the effect of automobile dynamic system for the power of wheel, and can be used for engine and brake performance research, normal pressure then reflects the impact of road surface for wheel, can be used for the research fields such as road spectrum collection.In order to ensure the precision of the tractive effort that Multi-component WFT resolves and normal pressure, filtering process must be carried out to the output signal of Multi-component WFT.
Conventional method is after having gathered multidimensional wheel force data, uses the method for wavelet analysis to carry out off-line filtering for data.Clearly there is two problems in the method, and one is that wavelet analysis cannot the processing signals problem identical with noise frequency range; Two is high accuracy wheel force datas that off-line filtering cannot obtain in real time.In order to solve this two problems, Kalman filter is introduced in the middle of the data processing of Multi-component WFT.But want to use Kalman filter, just must obtain state equation and the observational equation of Multi-component WFT, and due to the randomness of vehicle wheel forces and uncertainty, be difficult to construct state equation accurately.Want to design the high accuracy real time filter being applicable to Multi-component WFT, just must capture this technical bottleneck.
Summary of the invention
The technical problem that the present invention mainly solves is: for the deficiencies in the prior art, a kind of Real-Time Filtering method being applicable to Multi-component WFT is provided, the Real-Time Filtering of Multi-component WFT under dynamic environment can be applicable to, solve the problem of Multi-component WFT state equation structure difficulty, realize the real-time high-precision filtering of Multi-component WFT.
For solving the problems of the technologies described above, the technical scheme that the present invention adopts is: provide a kind of Real-Time Filtering method being applicable to Multi-component WFT, comprise the following steps:
(100) according to the operation principle of Multi-component WFT, the mathematical relationship expression formula between the output of setting up wheel-borne load and Multi-component WFT two passages;
(200) according to the mathematical relationship expression formula that step (100) is set up, confirm that the output of Multi-component WFT two passages meets at the uniform velocity turning motion track on two dimensional surface;
(300) output of Multi-component WFT two passages confirmed according to step (200) meets at the uniform velocity turning motion track on two dimensional surface, designs using at the uniform velocity turning motion model as Gauss's orthogonal integration point Kalman filter of state equation;
(400) the Gauss's orthogonal integration point Kalman filter designed by step (300) is adopted to carry out Real-Time Filtering to wheel-borne load.
In a preferred embodiment of the present invention, two passages of described Multi-component WFT are X passage and Y passage, and the mathematical relationship expression formula between the output of the wheel-borne load that step (100) is set up and Multi-component WFT two passages is:
（1）
In formula (1): F is wheel-borne load; F
for the output of Multi-component WFT X passage; F
for the output of Multi-component WFT Y passage; α is the angle of current time wheel-borne load and Multi-component WFT Y passage.
In a preferred embodiment of the present invention, when wheel rolling after an angle θ, output and the wheel-borne load of Multi-component WFT two passages meet following relationship:
（2）
In formula (2): F
for wheel rolling after angle θ, the output of Multi-component WFT X passage; F
for wheel rolling after an angle θ, the output of Multi-component WFT Y passage.
In a preferred embodiment of the present invention, from formula (1) and formula (2), at any time, the output of Multi-component WFT two passages all meets following relationship:
F
+F
=F （3）
In formula (3), F
for any time, the output of Multi-component WFT X passage; F
for any time, the output of Multi-component WFT Y passage;
Visible, when wheel rolling, the output two dimensional surface of Multi-component WFT two passages meets at the uniform velocity turning motion track.
In a preferred embodiment of the present invention, step (200) is specially: the mathematical relationship expression formula set up according to step (100), confirm the output of Multi-component WFT two passages, under Multi-component WFT coordinate system, meet planar circumferential motion characteristics.
In a preferred embodiment of the present invention, step (300) is specially: at the uniform velocity Turn Models will introduce Gauss's orthogonal integration point Kalman filter, and as the state equation of Gauss's orthogonal integration point Kalman filter, and select Systems with Linear Observation equation, using the observed quantity of the output of Multi-component WFT as Gauss's orthogonal integration point Kalman filter.
In a preferred embodiment of the present invention, further, using the state equation of horizontal turning model as Gauss's orthogonal integration point Kalman filter.
In a preferred embodiment of the present invention, the mathematic(al) representation of described horizontal turning model is:
(4)
The state equation FCT(ω of described horizontal turning model) be:
(5)
In formula (4),
, wk is white Gaussian noise, and in formula (5), T is the sampling time of system, and ω is the turning rate of wheel.
In a preferred embodiment of the present invention, the turning rate in described horizontal turning model is obtained by the angular velocity of rotation of wheel.
The invention has the beneficial effects as follows: by the output of Multi-component WFT, utilize Gauss's orthogonal integration point Kalman filter, obtain high-precision true wheel load values in real time; The Real-Time Filtering of Multi-component WFT under dynamic environment can be applicable to, solve the problem of Multi-component WFT state equation structure difficulty, realize the real-time high-precision filtering of Multi-component WFT.The method can be applied to the data filtering of the Multi-component WFT that Southeast China University's instrumental science and engineering college research and develop, and has very strong practicality.
Accompanying drawing explanation
Fig. 1 is a kind of structured flowchart being applicable to Real-Time Filtering method one preferred embodiment of Multi-component WFT of the present invention;
Fig. 2 is wheel-borne load of the present invention and Multi-component WFT output relation schematic diagram;
In figure: O-Multi-component WFT coordinate origin, X-Multi-component WFT X passage, Y-Multi-component WFT Y passage, F-wheel-borne load, the angle of α-current time wheel-borne load and Multi-component WFT Y passage, θ-wheel rolling angle.
Embodiment
Below in conjunction with accompanying drawing, preferred embodiment of the present invention is described in detail, can be easier to make advantages and features of the invention be readily appreciated by one skilled in the art, thus more explicit defining is made to protection scope of the present invention.
Refer to shown in Fig. 1 and Fig. 2, the embodiment of the present invention comprises:
Be applicable to a Real-Time Filtering method for Multi-component WFT, comprise the following steps:
(100) according to the operation principle of Multi-component WFT, the mathematical relationship expression formula between wheel-borne load (external force suffered by wheel: making a concerted effort of tractive effort and normal pressure) and the output of Multi-component WFT two passages is set up;
As shown in Figure 2, { OXY}, the initial point O of coordinate system are positioned at the center of the axle of wheel, and when wheel does not rotate, X-axis is parallel with ground level, are just with direction of advance to define Multi-component WFT coordinate system; Y-axis, perpendicular to ground level, is just with upward direction.The external force of definition suffered by wheel is making a concerted effort of F(tractive effort and normal pressure), the angle of F and Y-axis is α.The now X passage of Multi-component WFT and the output of Y passage is respectively:
（1）
F
for the output of Multi-component WFT X passage; F
for the output of Multi-component WFT Y passage; α is the angle of current time wheel-borne load and Multi-component WFT Y passage.
Wheel rotates along the direction of dotted arrow shown in Fig. 2, and at subsequent time, the angle that wheel turns over is θ, and the now X passage of Multi-component WFT and the output of Y passage is respectively:
（2）
(200) according to the mathematical relationship expression formula that step (100) is set up, confirm that the output of Multi-component WFT two passages meets at the uniform velocity turning motion track on two dimensional surface;
As can be seen from formula (1) and formula (2), at any time, the output of Multi-component WFT X passage and Y passage is all satisfied:
F
+F
=F （3）
As can be seen from formula (3), when wheel rolling, the output of Multi-component WFT X passage and Y passage { meets the characteristic of circular motion at coordinate system in OXY}.
(300) output of Multi-component WFT two passages confirmed according to step (200) meets at the uniform velocity turning motion track on two dimensional surface, designs using at the uniform velocity turning motion model as Gauss's orthogonal integration point Kalman filter of state equation;
Output due to Multi-component WFT two passages meets the characteristic of circular motion, Gauss's orthogonal integration point Kalman filter that it is state equation that the present invention devises with horizontal turning model.The mathematic(al) representation of horizontal turning model is as follows:
(4)
The state equation FCT(ω of described horizontal turning model) be:
(5)
In formula (4),
,
for white Gaussian noise; In formula (5), T is the sampling time of system, ω is the angular speed of vehicle wheel rotation, determine the horizontal turning model mentioned in formula (4) and formula (5), need to know turning rate ω in advance, in the present invention, turning rate ω can obtain conveniently by the angular velocity of rotation measuring wheel.
Because the derivative of the direct output and directly output that have employed transducer is quantity of state, so can directly select Systems with Linear Observation equation, its observational equation is as follows:
Z
k=H×X
k(6)
In formula (6):
(7)
(400) the Gauss's orthogonal integration point Kalman filter designed by step (300) is adopted to carry out Real-Time Filtering to wheel-borne load.Be specially: by formula (4) and formula (6) structure Gauss orthogonal integration point Kalman filter, real-time resolving can go out high-precision wheel force value.
Present invention is disclosed a kind of Real-Time Filtering method being applicable to Multi-component WFT, by the output of Multi-component WFT, utilize Gauss's orthogonal integration point Kalman filter, obtain high-precision true wheel load values in real time; The Real-Time Filtering of Multi-component WFT under dynamic environment can be applicable to, solve the problem of Multi-component WFT state equation structure difficulty, realize the real-time high-precision filtering of Multi-component WFT.The method can be applied to the data filtering of the Multi-component WFT that Southeast China University's instrumental science and engineering college research and develop, and has very strong practicality.
The foregoing is only embodiments of the invention; not thereby the scope of the claims of the present invention is limited; every utilize specification of the present invention and accompanying drawing content to do equivalent structure or equivalent flow process conversion; or be directly or indirectly used in other relevant technical fields, be all in like manner included in scope of patent protection of the present invention.
Claims (9)
1. be applicable to a Real-Time Filtering method for Multi-component WFT, it is characterized in that, comprise the following steps:
(100) according to the operation principle of Multi-component WFT, the mathematical relationship expression formula between the output of setting up wheel-borne load and Multi-component WFT two passages;
(200) according to the mathematical relationship expression formula that step (100) is set up, confirm that the output of Multi-component WFT two passages meets at the uniform velocity turning motion track on two dimensional surface;
(300) output of Multi-component WFT two passages confirmed according to step (200) meets at the uniform velocity turning motion track on two dimensional surface, designs using at the uniform velocity turning motion model as Gauss's orthogonal integration point Kalman filter of state equation;
(400) the Gauss's orthogonal integration point Kalman filter designed by step (300) is adopted to carry out Real-Time Filtering to wheel-borne load.
2. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 1, it is characterized in that, two passages of described Multi-component WFT are X passage and Y passage, and the mathematical relationship expression formula between the output of the wheel-borne load that step (100) is set up and Multi-component WFT two passages is:
（1）
In formula (1): F is wheel-borne load; F
for the output of Multi-component WFT X passage; F
for the output of Multi-component WFT Y passage; α is the angle of current time wheel-borne load and Multi-component WFT Y passage.
3. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 2, is characterized in that, when wheel rolling after an angle θ, output and the wheel-borne load of Multi-component WFT two passages meet following relationship:
（2）
In formula (2): F
for wheel rolling after angle θ, the output of Multi-component WFT X passage; F
for wheel rolling after an angle θ, the output of Multi-component WFT Y passage.
4. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 3, is characterized in that, from formula (1) and formula (2), at any time, the output of Multi-component WFT two passages all meets following relationship:
F
+ F
=F （3）
In formula (3), F
for any time, the output of Multi-component WFT X passage; F
for any time, the output of Multi-component WFT Y passage;
Visible, when wheel rolling, the output two dimensional surface of Multi-component WFT two passages meets at the uniform velocity turning motion track.
5. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 1, it is characterized in that, step (200) is specially: the mathematical relationship expression formula set up according to step (100), confirm the output of Multi-component WFT two passages, under Multi-component WFT coordinate system, meet planar circumferential motion characteristics.
6. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 1, it is characterized in that, step (300) is specially: at the uniform velocity Turn Models will introduce Gauss's orthogonal integration point Kalman filter, and as the state equation of Gauss's orthogonal integration point Kalman filter, and select Systems with Linear Observation equation, using the observed quantity of the output of Multi-component WFT as Gauss's orthogonal integration point Kalman filter.
7. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 6, is characterized in that, further, using the state equation of horizontal turning model as Gauss's orthogonal integration point Kalman filter.
8. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 7, it is characterized in that, the mathematic(al) representation of described horizontal turning model is:
(4)
The state equation F of described horizontal turning model
cT(ω) be:
(5)
In formula (4),
, w
kfor white Gaussian noise, in formula (5), T is the sampling time of system, and ω is the turning rate of wheel.
9. a kind of Real-Time Filtering method being applicable to Multi-component WFT according to claim 8, it is characterized in that, the turning rate ω in described horizontal turning model is obtained by the angular velocity of rotation of wheel.
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2015
- 2015-07-15 CN CN201510415068.0A patent/CN105007058A/en active Pending
Patent Citations (5)
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| CN1245287A (en) * | 1999-06-04 | 2000-02-23 | 合肥工业大学 | Real-time dynamic correcting system of multi-dimension force sensor |
| CN2421630Y (en) * | 2000-06-02 | 2001-02-28 | 哈尔滨工业大学 | Multidimensional sensor |
| CN101832837A (en) * | 2010-05-11 | 2010-09-15 | 东南大学 | Decoupling method for multidimensional force sensor based on coupling error modeling |
| CN102853967A (en) * | 2012-03-22 | 2013-01-02 | 东南大学 | Calculating method of initial values for multi-dimensional wheel force sensor |
| CN103454029A (en) * | 2013-09-03 | 2013-12-18 | 东南大学 | Linearity decoupling method based on kalman filter and repeated collection of multivariate force |
Non-Patent Citations (3)
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|---|
| DONG WANG 等: "Design of real-time filter for the wheel force transducer", 《SENSOR REVIEW》 * |
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