共查询到19条相似文献,搜索用时 531 毫秒
1.
首先对全维车速观测器进行降维处理,以减少观测器的在线计算量,并设计了非线性级联车速观测器.接着,对路面附着系数和轮胎侧偏刚度进行参数自适应估计,以提高质心侧偏角的估计精度,并基于HSRI轮胎模型设计了参数自适应非线性质心侧偏角观测器.在估算轮胎侧偏刚度时采用无侧向车速的车辆模型,以避免车辆动力学模型与侧向车速观测器的耦合作用,并引入带双重遗忘因子的递推最小二乘法,以保持算法的修正能力和解除不同估计参数之间误差的耦合作用.最后采用Simulink与Carsim动力学仿真软件进行联合仿真验证,结果表明所设计的参数自适应非线性质心侧偏角观测器是有效的,估计精度满足ESC控制的工程要求. 相似文献
2.
针对汽车状态估计中过程噪声和量测噪声统计特性不确定的状况,通过UKF算法与遗传算法相结合,提出一种新的自适应滤波算法,以降低噪声对估计结果的干扰。为达到较高的精度,建立了7自由度非线性车辆动力学模型,结合"魔术公式"轮胎模型对汽车行驶过程中的纵、侧向速度、轮胎力和质心侧偏角分别进行了估计。在利用UKF对汽车状态参数进行估计的同时,引入遗传算法,根据适应度函数对过程噪声和量测噪声进行寻优,实现了噪声的自适应作用,估计精度大幅提高。仿真和道路模拟试验的结果表明,UKF结合遗传算法的方法,能提高估计精度且具有很好的抗干扰性。 相似文献
3.
4.
5.
为了保证汽车的主动安全控制,需要准确地估计车辆行驶状态信息。针对目前汽车状态估计中由于技术条件限制和成本过高造成的部分参数无法测量或不易测量的问题,本文中利用低成本传感器,基于信息融合技术进行汽车行驶状态估计。建立了包括横摆、横向和纵向的3自由度非线性汽车动力学模型,同时为降低噪声对系统影响,建立了自适应无迹卡尔曼滤波(AUKF)的信息融合算法,给出车辆状态最小方差意义下的融合结果。利用纵向加速度、侧向加速度和转向盘转角等低成本传感器信号融合得到所需的难以测量的质心侧偏角、横摆角速度和纵向车速。通过Matlab/Simulink-CarSim联合仿真和实车试验对所研究的估计算法进行了试验验证。试验结果表明:该算法能够准确地估计汽车质心侧偏角、横摆角速度和纵向车速,且相比于无迹卡尔曼滤波(UKF),本算法提高了估计精度和实时性。 相似文献
6.
7.
《汽车安全与节能学报》2015,(1)
为了提高汽车质心侧偏角估计的准确性,提出了一种新的、基于运动学—动力学方法的融合估计方法。构建了质心侧偏角融合观测器(SAFO)。该SAFO包括3个子滤波器,每个子滤波器分别将横向车速的初步估计结果送到主滤波器中。主滤波器根据当前车辆行驶工况和融合规则,将子滤波器的估计结果融合成为全局意义下的质心侧偏角估计结果。结果表明:该SAFO具有良好的估计精度和长时间尺度下的计算稳定性,同时对横向加速度传感器偏差具有鲁棒性。因此,车辆测试数据验证了SAFO的性能。 相似文献
8.
9.
10.
11.
12.
The accurate estimation of sideslip angle is necessary for many vehicle control systems. The detection of sliding and skidding
is especially critical in emergency situations. In this paper, a sideslip angle estimation method is proposed that considers
severe longitudinal velocity variation over the short period of time during which a vehicle may lose stability due to sliding
or spinning. An extended Kalman filter (EKF) based on a kinematic model of a vehicle is used without initialization of the
inertial measurement unit to estimate vehicle longitudinal velocity. A dynamic compensation method that compensates for the
difference in the locations of the vehicle velocity sensor and the IMU in on-road vehicle tests is proposed. Evaluations with
a CarSim™ 27-degree-of-freedom (DOF) model for various vehicle test scenarios and with on-road tests using a real vehicle
show that the proposed sideslip angle estimation method can accurately predict sideslip angle, even when vehicle longitudinal
velocity changes significantly. 相似文献
13.
This paper presents a method that estimates the vehicle sideslip angle and a tire-road friction coefficient by combining measurements of a magnetometer, a global positioning system (GPS), and an inertial measurement unit (IMU). The estimation algorithm is based on a cascade structure consisting of a sensor fusing framework based on Kalman filters. Several signal conditioning techniques are used to mitigate issues related to different signal characteristics, such as latency and disturbances. The estimated sideslip angle information and a brush tire model are fused in a Kalman filter framework to estimate the tire-road friction coefficient. The performance and practical feasibility of the proposed approach were evaluated through several tests. 相似文献
14.
《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(2):127-147
Summary This paper details a novel method for measuring three key vehicle states – wheel slip, body sideslip angle, and tire sideslip angle – using GPS velocity information in conjunction with other sensors. Based on initial noise data obtained from the system components, a prediction of the accuracy of the angle measurements is obtained. These results demonstrate that the errors due to stochastic noise in the GPS signal are below one degree for meaningful vehicle speeds and approach a tenth of a degree at highway speeds. Hence the limiting factor for measuring these states is not the GPS receiver, but the manner in which other implementation issues – such as bias elimination, off-axis dynamics and dead-reckoning during loss of satellite visibility – are handled. Subsequent experiments validate both the error analysis and the methodology for obtaining the measurements. The experimental results for this preliminary implementation of GPS-based state estimation compare favorably to theoretical predictions, suggesting that this technique has potential for future implementation in vehicle diagnostic and, ultimately, safety systems. 相似文献
15.
This paper presents a novel nonlinear dynamic model of a multi-axle steering vehicle to estimate the lateral wear amount of tires. Firstly, a 3DOF nonlinear vehicle dynamic model is developed, including dynamic models of the hydropneumatic suspension, tire, steering system and toe angle. The tire lateral wear model is then built and integrated into the developed vehicle model. Based on the comparison of experimental and simulation results, the nonlinear model is proved to be better than a linear model for the tire wear calculation. In addition, the effects of different initial toe angles on tire wear are analyzed. As simulation results shown, the impact of the dynamic toe angle on the tire wear is significant. The tire wear amount will be much larger than that caused by normal wear if the initial toe angle increases to 1° - 1.5°. The results also suggest that the proposed nonlinear model is of great importance in the design and optimazation of vehicle parameters in order to reduce the tire wear. 相似文献
16.
《Vehicle System Dynamics: International Journal of Vehicle Mechanics and Mobility》2012,50(2):217-234
An adaptive sideslip angle observer considering tire–road friction adaptation is proposed in this paper. The single-track vehicle model with nonlinear tire characteristics is adopted. The tire parameters can be easily obtained through road test data without using special test rigs. Afterwards, this model is reconstructed and a high-gain observer (HGO) based on input–output linearisation is derived. The observer stability is analysed. Experimental results have confirmed that the HGO has a better computational efficiency with the same accuracy when compared with the extended Kalman filter and the Luenberger observer. Finally, a road friction adaptive algorithm based on vehicle lateral dynamics is proposed and validated through driving simulator data. As long as the tires work in the nonlinear region, the maximal friction coefficient could be estimated. This algorithm has excellent portability and is also suitable for other observers. 相似文献
17.
J. -S. Jo S. -H. You J. Y. Joeng K. I. Lee K. Yi 《International Journal of Automotive Technology》2008,9(5):571-576
The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize
dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to
enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into
a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based
on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake
pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle
and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance
of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental
results. 相似文献
18.
R. Chaichaowarat W. Wannasuphoprasit 《International Journal of Automotive Technology》2016,17(1):83-90
Vehicle yaw rate is a key parameter required for various active stability control systems. Accurate yaw rate information may be obtained from the fusion of some on-vehicle sensors and GPS data. In this study, the closed-form expression of the yaw rate–written as a function of front wheel rolling speeds and steering angle–was derived via kinematic analysis of a planar four-wheel vehicle on the assumption of no longitudinal slip at the both front tires. The obtained analytical solution was primarily verified by computational simulation. In terms of implementation, the 1:10th scaled rear-wheel-drive vehicle was modified so that the front wheel rolling speeds and the steering angle could be measured. An inertial measurement unit was also installed to provide the directly measured yaw rate used for validation. Preliminary experiment was done on some extremely random sideslip maneuvers beneath the global positioning using four recording cameras. Comparing with the vision-based and the gyro-based references, the vehicle yaw rate could be well approximated at any slip condition without requiring integration or vehicle and tire models. The proposed cost-effective estimation strategy using only on-vehicle sensors could be used as an alternative way to enhance performance of the GPS-based yaw rate estimation system while the GPS signal is unavailable. 相似文献
19.
The sideslip driving status is of fundamental importance to the stability of a vehicle. This paper presents a practical vehicle sideslip driving status estimation method that uses ESP (electronic stability program) sensors. ESP sensors such as wheel speed, lateral acceleration, yaw rate and steering wheel angle sensors are used to determine the sideslip driving status and distinguish a banked road. This estimation algorithm contains front-rear sideslip and banked road detection methods. The proposed sideslip estimation algorithm was designed to use the analytical redundancy of these sensors and Lagrange interpolation methods. The performance and effectiveness of the proposed estimation and compensation algorithm were investigated using vehicle tests. This paper presents the results of two cases that were used for the experimental verification: a curved flat road and banked road. 相似文献