通讯机构：
[Caixia Huang] H;Hunan Provincial Key Laboratory of Vehicle Power and Transmission System (Hunan Institute of Engineering), Xiangtan 411104, China
摘要：
Inconsistencies among battery cells and measurement errors have significant impacts on the accuracy and reliability of state of charge (SOC) estimations for series-connected battery packs. The aim of this paper is to propose a novel SOC estimation method for series-connected battery packs based on the fuzzy adaptive federated filtering. The mean-plus-difference model is employed to characterize the inconsistencies among battery cells. The fuzzy system is designed to improve the accuracy and adaptability of SOC estimation under cell inconsistencies. The SOC estimation value from a cell mean model and the standard deviation of SOC estimation are combined with a fuzzy system to determine their fusion weights. The master filter adaptively adjusts the information distribution coefficient according to the local filter estimation accuracy to improve reliability. Through simulation and experimentation on series-connected battery packs with different SOC distributions, the estimation accuracy of the proposed method is compared between the proposed method and the conventional methods. The SOC estimation accuracy of each battery cell is evaluated. The results show that, over the full SOC range, the root-mean-square error (RMSE) of the battery pack SOC estimation is less than 0.6% and 1.5% using online and offline parameters, respectively. The SOC estimation RMSEs of the battery cells using online and offline parameters are less than 0.4% and 1%, respectively. The fault tolerance is verified by artificially adding measurement errors. These accurate and reliable results show a strong prospect for the design and optimization of future clean and sustainable mobility.
关键词：
Braking-in-turn;braking performance;lateral stability;optimal slip ratio control;torque allocation control
摘要：
The active safety control of vehicles during braking-in-turn maneuver involves longitudinal and lateral dynamic control. The lateral stability and braking performance of vehicles can be ensured by properly coordinating the longitudinal and lateral forces of tires. In this study, a control system with a three-layer structure is used to achieve the above-mentioned purpose. The expected yaw rate and sideslip angle are adopted to calculate the direct yaw moment to guarantee the lateral stability of vehicles in the motion tracking layer. Considering the minimization of tire workload usage and braking force deviation as optimization objectives, torque allocation control is achieved for the direct yaw moment with lateral stability and the upper bound of longitudinal force (UBLF) of tires as constraint in the torque allocation layer. In the braking hydraulic pressure control layer, the hydraulic pressure in the wheel cylinder is adjusted according to the expected braking force of the wheel. This study proposes a method for determining the UBLF based on the optimal slip ratio (UBLF_OSR), which cannot only avoid obtaining the lateral force of tires but also directly restrict the distribution of tire force. The control system performance is analyzed on the basis of MATLAB/AMESim co-simulation. Results show that the proposed collaborative control strategy of lateral stability and braking performance ensures the lateral stability and braking performance during braking-in-turn maneuver.
期刊：
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING,2019年234(2-3):669-680 ISSN：0954-4070
通讯作者：
Wenguang Wu
作者机构：
[Huang, Caixia] College of Information, Mechanical and Electrical Engineering, Hunan International Economics University, Changsha, China;Hunan Provincial Key Laboratory of Intelligent Manufacturing Technology for High-Performance Mechanical Equipment, Changsha University of Science & Technology, Changsha, China;[Pan, Da; Wu, Wenguang] College of Automobile and Mechanical Engineering, Changsha University of Science & Technology, Changsha, China;[Zhang, Zhiyong] Hunan Provincial Key Laboratory of Intelligent Manufacturing Technology for High-Performance Mechanical Equipment, Changsha University of Science & Technology, Changsha, China<&wdkj&>College of Automobile and Mechanical Engineering, Changsha University of Science & Technology, Changsha, China
通讯机构：
[Wenguang Wu] C;College of Automobile and Mechanical Engineering, Changsha University of Science & Technology, Changsha, China
关键词：
Operational transfer path analysis;vibration source identification;contribution analysis;heavy commercial vehicle;cab mount system
摘要：
Operational transfer path analysis is applied in this study to identify the vibration source and its critical transfer path. A simple analytical five-degrees-of-freedom mechanical isolation system is first taken as an example to illustrate the analysis flow and to validate the accuracy of operational transfer path analysis. The acceleration amplitude spectrum of the receiver is used to prove the accuracy, and the path contribution of each path is used to identify the critical path. Operational transfer path analysis is then applied to the cab mount system of a heavy commercial vehicle to identify the vibration source and its critical transfer path. The vibration energy propagation capabilities from the four cab mounts to the driver’s seat are analyzed by operational transfer path analysis with the path contribution analysis, and the maximum vibration source is identified by the path operation contribution analysis. The analysis and evaluation method of the operational transfer path analysis introduced in this study can provide a research foundation and reference for vibration or noise source identification in mechanical systems.
关键词：
Electric vehicle;power performance;motor modeling;brushless DC motor;parameter determination
摘要：
The analysis and control of powertrain systems of electric vehicle, which is an important type of new energy vehicle, have been the focus of extensive research, but determining the motor modeling parameters remains a problem. A method of parameter determination for brushless DC motor modeling based on vehicle power performance was developed in this study. The power and torque of the driving motor of an electric vehicle were obtained by using the dynamic equation of the electric vehicle to satisfy the requirements of power performance. The ranges of the back electromotive force coefficient and the winding inductance were derived from the voltage and dynamic equations of brushless DC motor, which were deduced from the expected power and torque of the motor. The modeling parameters were then determined on the basis of the influence of power source voltage, back electromotive force coefficient, winding inductance, and winding resistance on vehicle power performance. A hardware-in-loop simulation of vehicle power performance was performed to verify the effectiveness of the proposed method. Results indicate that the maximum vehicle velocity is 172 km/h, and the acceleration time of 100 km/h is 13 s, which reveal that the motor modeling parameters obtained with the method satisfy relevant requirements.
摘要：
Vehicle state is essential for active safety stability control. However, the accurate measurement of some vehicle states is difficult to achieve without the use of expensive equipment. To improve estimation accuracy in real time, this paper proposes an estimator of vehicle velocity based on the adaptive unscented Kalman filter (AUKF) for an in-wheel-motored electric vehicle (IWMEV). Given the merits of an independent drive structure, the tire forces of the IWMEV can be directly calculated through a vehicle dynamic model. Additionally, by means of the normalized innovation square, the validity of vehicle velocity estimation can be detected, and the sliding window length can be adjusted adaptively; thus, the steady-state error and the dynamic performance of the IWMEV are demonstrated to be simultaneously improved over an alternative approach in comparisons. Then, an adaptive adjustment strategy for the noise covariance matrices is introduced to overcome the impact of parameter uncertainties. The numerically simulated and experimental results prove that the proposed vehicle velocity estimator based on AUKF not only improves estimation accuracy but also possesses strong robustness against parameter uncertainties. The deployment of the estimation algorithm by using a single-chip microcomputer verifies the strong real-time performance and easy-to-implement characteristics of the proposed algorithm.
作者机构：
[唐磊] College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China;[郝威; 袁泉] State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China;[张志勇] College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China<&wdkj&>State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China
作者机构：
工程车辆安全性设计与可靠性技术湖南省重点实验室, 工程车辆安全性设计与可靠性技术湖南省重点实验室, 长沙, 410114;长沙理工大学汽车与机械工程学院, 长沙, 410114;湖南大学机械与运载工程学院, 长沙, 410082;[张志勇] Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle, Changsha, 410114, China<&wdkj&>College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China;[张淑芝; 张刘铸; 李博浩] College of Automobile and Mechanical Engineering, Changsha University of Science and Technology, Changsha, 410114, China
通讯机构：
Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle, Changsha, China
通讯机构：
Changsha University of Science and Technology, Hunan Province Key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle, Changsha, China
