基于信息融合技术的线控汽车状态和路面参数的仿真估算与实验研究
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摘要
随着信息融合技术的广泛应用,其算法日趋成熟。线控汽车作为概念全新的车辆,其安全性尤为重要,必须根据当前的车辆状态和环境信息以及驾驶员意图控制决策车辆的行驶路径,以保证线控汽车的主动安全性。本文提出了利用信息融合中的卡尔曼滤波算法通过建模估算出车辆状态和路面附着系数,并应用到线控车转向控制策略中,从而为提高线控汽车的安全性奠定基础。
本文以三自由度车辆动力学模型为基础,利用线性、非线性轮胎动力学模型,分别建立了经典卡尔曼、扩展卡尔曼、双重扩展卡尔曼估计汽车状态和路面附着系数的递推估算模型,同时提出了基于车辆状态及反馈的线控汽车转向控制策略,并分别在CarSim车辆软件、自行设计的线控汽车仿真试验台和实车试验进行验证。结果表明,所提出的估算方法能准确估计车辆状态和路面参数。
本文的创新之处在于通过双重扩展卡尔曼算法,实时、准确地估算出车辆状态与路面参数的变化,并将其应用到线控汽车转向控制策略中,使线控汽车具有更高的主动安全性和易驾驶性。同时本文为研究的需要还设计了线控汽车仿真试验台。
Information fusion, an automated comprehensive information processing technology, has had significant development in the last decade. The technology provides more comprehensive, reliable and accurate signal source through the integration of real-time, redundant or complementary signals provided by multiple sensors, so as to guarantee the enhancement of system performance. On the other hand, along with the rapid development of electrical-electronic technology and the micro-processing technology,Steer–by-wire, as a new generation of automotive mechatronics control technology, has been increasingly attracted attentions from the world's major automobile manufacturers. One of the key technologies for practical real-time access of Steer–by-wire vehicle to motor sport is the motion state and road status information. As the number of vehicle states and road condition information (such as side slip Angle, road tire friction coefficient, etc.) are difficult and costly to obtain accurately. Researches on how to obtain accurate state of vehicle and road state estimation algorithm and put it into practical use for steer–by-wire vehicle have important theoretical and engineering significance.
Based on the steering control information fusion theory, this paper proposed to use a decoupled extended Kalman filtering technique to achieve steering control of steer–by-wire vehicle and accurate estimation the state of motion and road tire friction coefficient, which has been broadly tested by a test-bed. The main contribution of this paper are as follows:
1、steer–by-wire vehicle steering control Control Strategy
Steering performance is an important evaluation criterion of steer–by-wire vehicle performance, it directly affects the handling and stability capability of steer–by-wire vehicle. To ensure safe driving of vehicles, reducing traffic accidents plays an important role. Due to the cancellation of the fixed connection between the steering wheel and front wheel steering mechanism (ie, steering ratio is no longer a fixed value), steering ratio is changed to ensure the yaw rate gain G~r_(δ_(sw)) on the steering wheel angle to be always a fixed value. The steer–by-wire simulation test-bed test verification shows that when G~r_(δ_(sw)) is 0.5, the driver has the best subjective feeling, and can adapt to a variety of speed and driving conditions. Based on this theory, the yaw rate and lateral acceleration feedback steering control strategy are integrated to verify different road adhesion coefficient respectively. Testing results show that the use of fixed gain of yaw rate and yaw rate and lateral acceleration feedback control can improve the steer–by-wire vehicle control and stability, and reduce driver’s burden.
2、The application of information fusion on estimation algorithm of steer–by-wire vehicle status parameters and road tire friction coefficient
On steer–by-wire vehicle steering control strategy, various types of state parameters of vehicles and roads are needed to be estimated. This paper adopts information fusion technology,in using of Kalman filter theory for rapid simulation and estimation of these parameters. Using different vehicles model and tire model, the classical Kalman filter, extended Kalman filter, the decouple extended Kalman filter recursive estimation models are established and verified. Experimental results show that dynamic model based on three degrees of freedom, using the HSRI tire model of a decouple extended Kalman filter, not only accurately estimates the vehicle state parameters, but also estimates the road tire friction coefficient in real-time. Road tire friction coefficient is difficult to measure in practice, but it is essential to control steer–by-wire vehicle. When there are changes on road, steer–by-wire vehicle control strategies must be changed accordingly. In the decouple extended Kalman filter, two recursive state and parameter estimation model exists in parallel, while they are dependent on each other, and has real-time interaction correction to forecast information, which quickly converges towards estimated true value for simulation. The accurate estimation of decouple extended Kalman filter theory in the vehicle state and road information make it possible that some of the parameters can be estimated, which is proved to be difficult to obtain, and it also provides the necessary conditions for steer–by-wire vehicle steering control strategy. In the meantime, the validity and feasibility of this algorithm have been verified by steer–by-wire simulation and the real vehicle test-bed venue.
3、Steer–by-wire simulation test-bed software and hardware design
In this paper, a steer–by-wire simulation test-bed is proposed, which is composed of two parts, namely test-bed hardware and software. For software designation, real-time computing power steering models, data acquisition system and control the caller are proposed. For hardware designation, real steer–by-wire system, drivers operating systems, instrument show the simulated system are proposed. Steer–by-wire simulation test-bed is developed for the driver in order that a real operating environment is provided, in which the estimation results of parameters and state is more similar with the actual vehicle condition. This paper focuses on the simulation test-bed signal acquisition and control methods and drive control algorithms, including stalls, pedal displacement, ignition, steering, steering wheel angle etc; analog, digital acquisition card and timing card driver control algorithm preparation. From this research, a real driver, steer–by-wire system hardware and real-time dynamic model of the organic integration are achieved. The entire test-bed provides a person - Vehicle Hardware-in-loop simulation platform, on which experiments can be carried out without danger to any limits of environmental conditions. Sufficient preparatory works have also been done for the real vehicle field test
4. steer–by-wire vehicle status parameters and the road tire friction coefficient estimation algorithm validation
Using the theory of information fusion technology to model the simulation, this paper respectively controlled steer–by-wire simulation test-bed and give real vehicle field test validation. During the steer–by-wire simulation test-bed, we propose to use Carsim vehicle dynamics model and the matlab built under the Simulink simulation model state estimation, real-time interactive vehicle status information, the vehicle and road condition are then estimated. Test-bed experimental results show that the algorithm is able to precisely estimate the speed, centroid lateral angle, road tire friction coefficient and other state parameters. The validity and accuracy of the proposed estimation algorithms are also verified by field test using real vehicle data.
The novelty of this paper is that we propose to use decoupled extended Kalman filter theory to accurately estimate the vehicle state parameters and road tire friction coefficient, the proposed estimation algorithm is able to estimate the state parameters, including vehicle speed, lateral acceleration, yaw rate and the road tire friction coefficient etc. Estimation results are applied to steer–by-wire vehicle steering control feedback strategy to improve the active operation safety of steer–by-wire vehicle. This paper also designed a steer–by-wire simulation test-bed software and hardware equipment, which is proved to be a good platform for fugure research on steer–by-wire vehicle theory. We design a set of wheel speed signal acquisition methods, which is proved to able to accurately capture the vehicle speed signal. The proposed research achievements lay the foundation for the theoretical and practical development of steer-by-wire vehicle in the future.
本文以三自由度车辆动力学模型为基础,利用线性、非线性轮胎动力学模型,分别建立了经典卡尔曼、扩展卡尔曼、双重扩展卡尔曼估计汽车状态和路面附着系数的递推估算模型,同时提出了基于车辆状态及反馈的线控汽车转向控制策略,并分别在CarSim车辆软件、自行设计的线控汽车仿真试验台和实车试验进行验证。结果表明,所提出的估算方法能准确估计车辆状态和路面参数。
本文的创新之处在于通过双重扩展卡尔曼算法,实时、准确地估算出车辆状态与路面参数的变化,并将其应用到线控汽车转向控制策略中,使线控汽车具有更高的主动安全性和易驾驶性。同时本文为研究的需要还设计了线控汽车仿真试验台。
Information fusion, an automated comprehensive information processing technology, has had significant development in the last decade. The technology provides more comprehensive, reliable and accurate signal source through the integration of real-time, redundant or complementary signals provided by multiple sensors, so as to guarantee the enhancement of system performance. On the other hand, along with the rapid development of electrical-electronic technology and the micro-processing technology,Steer–by-wire, as a new generation of automotive mechatronics control technology, has been increasingly attracted attentions from the world's major automobile manufacturers. One of the key technologies for practical real-time access of Steer–by-wire vehicle to motor sport is the motion state and road status information. As the number of vehicle states and road condition information (such as side slip Angle, road tire friction coefficient, etc.) are difficult and costly to obtain accurately. Researches on how to obtain accurate state of vehicle and road state estimation algorithm and put it into practical use for steer–by-wire vehicle have important theoretical and engineering significance.
Based on the steering control information fusion theory, this paper proposed to use a decoupled extended Kalman filtering technique to achieve steering control of steer–by-wire vehicle and accurate estimation the state of motion and road tire friction coefficient, which has been broadly tested by a test-bed. The main contribution of this paper are as follows:
1、steer–by-wire vehicle steering control Control Strategy
Steering performance is an important evaluation criterion of steer–by-wire vehicle performance, it directly affects the handling and stability capability of steer–by-wire vehicle. To ensure safe driving of vehicles, reducing traffic accidents plays an important role. Due to the cancellation of the fixed connection between the steering wheel and front wheel steering mechanism (ie, steering ratio is no longer a fixed value), steering ratio is changed to ensure the yaw rate gain G~r_(δ_(sw)) on the steering wheel angle to be always a fixed value. The steer–by-wire simulation test-bed test verification shows that when G~r_(δ_(sw)) is 0.5, the driver has the best subjective feeling, and can adapt to a variety of speed and driving conditions. Based on this theory, the yaw rate and lateral acceleration feedback steering control strategy are integrated to verify different road adhesion coefficient respectively. Testing results show that the use of fixed gain of yaw rate and yaw rate and lateral acceleration feedback control can improve the steer–by-wire vehicle control and stability, and reduce driver’s burden.
2、The application of information fusion on estimation algorithm of steer–by-wire vehicle status parameters and road tire friction coefficient
On steer–by-wire vehicle steering control strategy, various types of state parameters of vehicles and roads are needed to be estimated. This paper adopts information fusion technology,in using of Kalman filter theory for rapid simulation and estimation of these parameters. Using different vehicles model and tire model, the classical Kalman filter, extended Kalman filter, the decouple extended Kalman filter recursive estimation models are established and verified. Experimental results show that dynamic model based on three degrees of freedom, using the HSRI tire model of a decouple extended Kalman filter, not only accurately estimates the vehicle state parameters, but also estimates the road tire friction coefficient in real-time. Road tire friction coefficient is difficult to measure in practice, but it is essential to control steer–by-wire vehicle. When there are changes on road, steer–by-wire vehicle control strategies must be changed accordingly. In the decouple extended Kalman filter, two recursive state and parameter estimation model exists in parallel, while they are dependent on each other, and has real-time interaction correction to forecast information, which quickly converges towards estimated true value for simulation. The accurate estimation of decouple extended Kalman filter theory in the vehicle state and road information make it possible that some of the parameters can be estimated, which is proved to be difficult to obtain, and it also provides the necessary conditions for steer–by-wire vehicle steering control strategy. In the meantime, the validity and feasibility of this algorithm have been verified by steer–by-wire simulation and the real vehicle test-bed venue.
3、Steer–by-wire simulation test-bed software and hardware design
In this paper, a steer–by-wire simulation test-bed is proposed, which is composed of two parts, namely test-bed hardware and software. For software designation, real-time computing power steering models, data acquisition system and control the caller are proposed. For hardware designation, real steer–by-wire system, drivers operating systems, instrument show the simulated system are proposed. Steer–by-wire simulation test-bed is developed for the driver in order that a real operating environment is provided, in which the estimation results of parameters and state is more similar with the actual vehicle condition. This paper focuses on the simulation test-bed signal acquisition and control methods and drive control algorithms, including stalls, pedal displacement, ignition, steering, steering wheel angle etc; analog, digital acquisition card and timing card driver control algorithm preparation. From this research, a real driver, steer–by-wire system hardware and real-time dynamic model of the organic integration are achieved. The entire test-bed provides a person - Vehicle Hardware-in-loop simulation platform, on which experiments can be carried out without danger to any limits of environmental conditions. Sufficient preparatory works have also been done for the real vehicle field test
4. steer–by-wire vehicle status parameters and the road tire friction coefficient estimation algorithm validation
Using the theory of information fusion technology to model the simulation, this paper respectively controlled steer–by-wire simulation test-bed and give real vehicle field test validation. During the steer–by-wire simulation test-bed, we propose to use Carsim vehicle dynamics model and the matlab built under the Simulink simulation model state estimation, real-time interactive vehicle status information, the vehicle and road condition are then estimated. Test-bed experimental results show that the algorithm is able to precisely estimate the speed, centroid lateral angle, road tire friction coefficient and other state parameters. The validity and accuracy of the proposed estimation algorithms are also verified by field test using real vehicle data.
The novelty of this paper is that we propose to use decoupled extended Kalman filter theory to accurately estimate the vehicle state parameters and road tire friction coefficient, the proposed estimation algorithm is able to estimate the state parameters, including vehicle speed, lateral acceleration, yaw rate and the road tire friction coefficient etc. Estimation results are applied to steer–by-wire vehicle steering control feedback strategy to improve the active operation safety of steer–by-wire vehicle. This paper also designed a steer–by-wire simulation test-bed software and hardware equipment, which is proved to be a good platform for fugure research on steer–by-wire vehicle theory. We design a set of wheel speed signal acquisition methods, which is proved to able to accurately capture the vehicle speed signal. The proposed research achievements lay the foundation for the theoretical and practical development of steer-by-wire vehicle in the future.
引文
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