本文關鍵詞： 駕駛員模型 多點預瞄 線性二次型 神經(jīng)肌肉系統(tǒng) 車輛穩(wěn)定性 仿真　出處：《南京航空航天大學》2014年碩士論文　論文類型：學位論文

【摘要】：駕駛員駕駛機動車時，因個人自身因素引起的道路交通安全事故發(fā)生頻繁，駕駛員的駕駛行為，是誘發(fā)交通事故的主要原因，如何對駕駛員轉(zhuǎn)向行為特性進行分析與研究進而營造一個安全、舒適的駕駛環(huán)境也就成為了目前研究的熱點。鑒于目前采用車輛測試成本較高、時間長、同時還會受到空間等環(huán)境條件的限制等因素的影響，在這種情況下建立精確、合理、符合駕駛員特性的駕駛員轉(zhuǎn)向控制模型，對于車輛實車試驗驗證與分析、車輛輔助設計及確保行車安全具有重要意義。 本文針對駕駛員轉(zhuǎn)向行為所涉及的問題，，對基于線性二次型（LQR）的駕駛員轉(zhuǎn)向控制模型、神經(jīng)肌肉動態(tài)性模型及車輛穩(wěn)定性控制模型等內(nèi)容進行了較深入的研究，其具體研究內(nèi)容可以歸納如下： 首先，設計了基于線性二次型（LQR）并考慮駕駛員延時特性的駕駛員轉(zhuǎn)向控制模型。針對駕駛員轉(zhuǎn)向控制方法進行研究，根據(jù)車輛動力學及線性規(guī)劃最優(yōu)控制理論，采用多點預瞄機制建立了“最優(yōu)-預瞄”駕駛員轉(zhuǎn)向控制模型。針對不同控制權(quán)值進行控制軌跡跟隨性能的分析。根據(jù)反饋矩陣系數(shù)來探究最優(yōu)駕駛員的內(nèi)在駕駛特性。采用狀態(tài)移位寄存器的形式將駕駛員延時特性考慮到駕駛員轉(zhuǎn)向控制模型中，使設計的模型更貼近實際駕駛員轉(zhuǎn)向行為特性。采用雙移線的仿真方法驗證該駕駛員轉(zhuǎn)向控制模型的有效性。 其次，將神經(jīng)肌肉動態(tài)性模型融合到駕駛員轉(zhuǎn)向控制模型中。根據(jù)神經(jīng)肌肉具體作用過程及肌肉的反應反射的內(nèi)在機理，設計了手臂轉(zhuǎn)向動態(tài)性模型與神經(jīng)肌肉控制環(huán)節(jié)構(gòu)成的神經(jīng)肌肉動態(tài)性模型。其中神經(jīng)肌肉控制環(huán)節(jié)包含反射控制、剛度因子與參考模型三部分，并得到各部分模型或傳遞函數(shù)的具體形式：根據(jù)手臂及車輛轉(zhuǎn)向系統(tǒng)的動態(tài)耦合性，得到手臂轉(zhuǎn)向動態(tài)性模型的運動方程；通過肌肉協(xié)同收縮得到剛度因子；通過系統(tǒng)辨識的方法得到了耦合的駕駛員、車輛及轉(zhuǎn)向系統(tǒng)之間肌肉力矩及轉(zhuǎn)向角之間的傳遞函數(shù)，從而得到內(nèi)部參考模型�？紤]了轉(zhuǎn)向力矩反饋對駕駛員神經(jīng)肌肉動態(tài)性的影響，將神經(jīng)肌肉動態(tài)性模型融合到駕駛員轉(zhuǎn)向控制模型中，并進行仿真分析。通過仿真驗證神經(jīng)肌肉動態(tài)性參數(shù)對車輛轉(zhuǎn)向及軌跡跟蹤性能的影響。 最后，在包含神經(jīng)肌肉動態(tài)性的駕駛員轉(zhuǎn)向控制模型的基礎上，提出建立車輛穩(wěn)定性控制模型。考慮到輪胎的非線性特性，基于“魔術(shù)公式”及車輛動力學建立了整車動力學模型。根據(jù)車輛的線性動力學模型及線性二次型最優(yōu)控制理論，采用橫擺角速度和質(zhì)心側(cè)偏角作為控制變量，建立一種增加附加橫擺力矩的穩(wěn)定性控制模型將其應用到整車動力學模型中，并進行仿真驗證。驗證該穩(wěn)定性控制模型能夠保證車輛在不同附著系數(shù)路面上的穩(wěn)定性。 綜上所述，本文一方面設計了駕駛員轉(zhuǎn)向控制模型，通過雙移線仿真實驗，驗證不同控制權(quán)值下的軌跡跟蹤性能，控制效果較好，以選取最優(yōu)的駕駛員轉(zhuǎn)向控制模型。另一方面將神經(jīng)肌肉動態(tài)性模型融合到駕駛員轉(zhuǎn)向控制模型中，研究結(jié)果表明駕駛員神經(jīng)肌肉動態(tài)性參數(shù)（反射增益、剛度因子）及內(nèi)部參考模型的精確性，對于車輛軌跡跟蹤性能具有重要影響。在此基礎上，建立了車輛穩(wěn)定性控制模型，不僅提高了車輛在不同附著系數(shù)路面上的穩(wěn)定性，而且其研究結(jié)果在相關領域中有較重要的理論意義和工程應用價值。
[Abstract]:The driver when driving the motor vehicle, road traffic safety accidents caused by the personal factors of the frequent occurrence of the driving behavior, is mainly caused by traffic accidents, how to driver steering behavior analysis and research and to create a safe, comfortable driving environment has become the hotspot of the research. In view of the vehicle test of high cost, long time, but also by the influence of space environment conditions and other factors, in this case to establish accurate, reasonable, accord with the characteristics of drivers driver for vehicle steering control model, vehicle test and analysis, has the important meaning of vehicle design and ensure traffic safety.
Aiming at the problems involved in driver's steering behavior, this paper makes a deep research on driver's steering control model based on linear two times (LQR), neuromuscular dynamic model and vehicle stability control model, etc. the specific research contents can be summarized as follows:
First of all, the design based on the linear two type (LQR) and considering the delay characteristics of the driver steering control model. According to the driver's steering control method is studied, according to the vehicle dynamics and linear programming optimal control theory, established the "best - Preview" driver steering control model using multipoint Preview for different control mechanisms. Weight control analysis of trajectory following performance. According to the internal driving characteristics to explore the optimal feedback matrix coefficients of the driver. The state of the shift register form driver delay characteristics considering the driver's steering control model, the design of the model closer to the actual driver steering behavior. The simulation method using double lane change to verify that the driver's steering effectiveness control model.
Secondly, the fusion of nerve muscle dynamic model to the driver's steering control model. According to the internal mechanism of reaction process and the specific role of reflex muscle muscle, the steering arm design of nerve muscle model dynamic model and a dynamic neuromuscular control link. The neuromuscular control link includes reflection control, stiffness factor with the three parts of the reference model, and get the specific form of each part of the model or the transfer function: according to the dynamic coupling system of vehicles and arms, arm steering motion equation obtained dynamic model; CO contraction stiffness factor by muscle; through the method of system identification has been coupled to the driver, vehicle and steering system. Muscle torque and steering angle between the transfer function, so as to obtain the internal reference model. Considering the steering torque feedback to the driver by God The influence of muscle dynamics is integrated into the driver's steering control model, and the simulation analysis is carried out. The influence of neuro muscular dynamic parameters on vehicle steering and trajectory tracking performance is verified by simulation.
Finally, the dynamic nature of the nerve muscle contains the driver's steering control based on the model, proposed the establishment of vehicle stability control model. Considering the nonlinear characteristics of tires, based on the "magic formula" and vehicle dynamics vehicle dynamic model has been established. According to the linear dynamics model and linear vehicle two optimum control theory, the yaw angle speed and sideslip angle as control variables, establish a stability of additional yaw moment control model is applied to the vehicle dynamics model, and simulation. Verify the stability control model can ensure the vehicle stability with different adhesion coefficient road.
In summary, this paper designed a driver steering control model, through the double lane change simulation, verify the tracking performance under different weight control trajectory, good control effect, to select the best driver steering control model. On the other hand the fusion neuromuscular dynamic model to the driver's steering control model, the results show that the nerve muscle the dynamic parameters (reflection gain, stiffness factor) accuracy and internal reference model, has an important effect on the tracking performance of the vehicle trajectory. On this basis, establish a vehicle stability control model not only improves the stability of the vehicle in different attachment coefficient road, and the research results have important theoretical significance and engineering the application value in related fields.

【學位授予單位】：南京航空航天大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U491.25

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