【摘要】：運(yùn)用現(xiàn)代控制理論解決實(shí)時(shí)道路坡度估計(jì)問題時(shí)通常假設(shè)道路坡度是不變的,雖然道路坡度相比于其他車輛狀態(tài)參數(shù)是緩慢變化的,但是完全忽略道路坡度變化率特征會(huì)造成較大的時(shí)間延遲。為了彌補(bǔ)這一缺點(diǎn),本文運(yùn)用縱向加速度傳感器表達(dá)了道路坡度的變化率信息,在此基礎(chǔ)上建立了車輛速度、加速度與道路坡度的狀態(tài)轉(zhuǎn)移關(guān)系,從而構(gòu)建了坡度估計(jì)卡爾曼濾波器。試驗(yàn)結(jié)果表明,考慮道路坡度變化率能有效降低道路坡度在線估計(jì)的延遲現(xiàn)象。
[Abstract]:When using modern control theory to solve the real-time road slope estimation problem, it is usually assumed that the road slope is invariant, although the road slope changes slowly compared with other vehicle state parameters. However, ignoring the characteristics of road slope change rate will result in a large time delay. In order to make up for this shortcoming, this paper uses the longitudinal acceleration sensor to express the change rate information of the road slope, and on this basis, establishes the state transfer relation between the vehicle speed, acceleration and the road slope. Thus the Kalman filter for slope estimation is constructed. The experimental results show that the delay in on-line estimation of road slope can be effectively reduced by considering the change rate of road slope.
【作者單位】： 吉林大學(xué)交通學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(51475199)
【分類號(hào)】：U463.6;U495

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本文編號(hào)：2304921