Road surface state estimation method and road surface state estimation device
A technology for road surface state estimation and road surface state, which is applied in the direction of brakes, etc., can solve the problem of reducing the degree of freedom of the tread pattern
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Embodiment approach 1
[0063] figure 1 It is a functional block diagram of the road surface state estimation apparatus 10 according to Embodiment 1 of the present invention.
[0064] The road surface state estimation apparatus 10 includes an acceleration sensor 11 as an unsprung front and rear acceleration detection means, a wheel speed sensor 12 as a wheel speed detection means, a wheel speed change amount calculation means 13, a variation range calculation means 14, a storage means 15, and a road surface state estimation means Part 16. Note that each part of the wheel speed change amount calculation part 13 to the road surface state estimation part 16 may be constituted by computer software, for example.
[0065] like figure 1 As shown, the acceleration sensor 11 mounted to the steering knuckle 31 detects the unsprung front and rear acceleration G x . The steering knuckle 31 is a non-rotating side member (vehicle unsprung member) of the wheel unit 30 connected to the hub 33 which rotates tog...
Embodiment 1
[0090] A vehicle was prepared in which the left front wheel was equipped with a studless tire with a tire size of 225 / 55R17 and the steering knuckle of the left front wheel was equipped with an acceleration sensor. Make the vehicle run at a predetermined speed (30km / h~80km / h) on smooth roads (smooth paved roads and icy roads), roads with more bumps (drainage paved roads) and uneven roads, calculated by the research institute The variation range σ(ΔV w ) and the variation range σ(G x )The relationship between. exist figure 2 These results are shown in (a) and (b).
[0091] Note that the range of variation figures are calculated for every 6.5 meters of travel.
[0092] In addition, the wheel speed information of the left wheel is obtained from the vehicle information system (CAN line).
[0093] exist figure 2 In (a) and (b), the horizontal axis represents σ(ΔV w ), and the vertical axis represents σ(G x ). Lighter circles represent data for smooth paved roads, darker ...
Embodiment approach 2
[0098] In Embodiment 1 described above, the state of the road surface during travel is estimated to be one of a smooth road, a road with many irregularities, and an uneven road. However, if image 3 As shown, the road surface state estimating device 10Y equipped with the acceleration sensor 11 for detecting the unsprung front-rear acceleration and the second acceleration sensor 11Y as the unsprung lateral acceleration detecting means on the steering knuckle 31 can be used to estimate the Whether the estimated smooth road is a smooth paved road with a large road surface friction coefficient μ (μ>0.7) or a smooth icy road (ice slope) with a small road surface friction coefficient μ (μ<0.2).
[0099] Note that, as the acceleration sensor 11, a sensor capable of detecting acceleration in two directions, that is, an unsprung front-rear acceleration G, can be used. x and unsprung lateral acceleration G y the acceleration sensor.
[0100] The road surface state estimating device 1...
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