Table of Content

10 August 2018, Volume 29 Issue 15

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Study on Multi-Agent System of Energy Managements for 4WD Electric Vehicles

YIN Guodong, LI Guangmin, ZHU Tong, CHEN Jiansong

2018, 29(15):  1765-1771. 

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In order to explore the energy flow relationship of each electricity system of 4WD electric vehicles， a framework of energy managements for 4WD electric vehicles was structured based on multi-Agent system， and details of this framework were described. A mathematical model of multi-Agent system for energy managements was built with a decision-planning layer based on state transition and transferable belief model. The models of multi-Agent system for energy managements were built in Netlogo， and the energy configuration status was simulated under the rapid acceleration working conditions of electric vehicles using Netlogo. It indicates that the framework of the built energy management multi-Agent system may adjust the energy distribution weights of each Agent dynamically， and the energy allocation of each Agent maybe coordinated reasonably on the premise of satisfying dynamics requirements.

Rollover Stability and Control of In-wheel Motor Drive Electric Vehicles

JIN Zhilin, CHEN Guoyu, ZHAO Wanzhong

2018, 29(15):  1772-1779. 

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To figure out the non-linear relationship between the unsprung mass and rollover stability of in-wheel motor drive electric vehicles， the effects of the unsprung mass on rollover stability in different road excitations were analyzed and an anti-rollover control strategy was investigated. First， taking the characteristics of four-wheel independent drive into consideration， the rollover dynamics vehicle models including the active suspension were established， and the rollover index suitable for uneven road was determined. Next， taking an in-wheel motor drive SUV as an example， the effects of unsprung mass on the vehicle roll stability were verified respectively. Finally， hierarchical controllers were designed based on the distributions of the four wheels driving torques. And some simulation tests with typical manoeuvres were also conducted to evaluate the proposed control method. The results show that， the unsprung mass and the rollover stability form a normal distribution on flat road， however， once existing road excitation， there is complex coupling relationship among the effects of unsprung mass and rollover stability. With the hierarchical rollover prevention controller， the vehicle rollover maybe avoided effectively.

Vehicle Stability Control of Distributed-driven Electric Vehicles Based on Optimal Torque Allocation

ZHANG Xizheng, ZHENG Liang

2018, 29(15):  1780-1787. 

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A hierarchical vehicle-stability-control method was presented based on the longitudinal force distribution optimization for the handling and stability control of the distributed-driven electric vehicles. The eight-degree-freedom vehicle models and the three-layer control systems were developed. By selecting the sideslip angle and the yaw rate as the state variables and introducting the virtual control to decouple two control variables，  the integral 2-DOF vehicle models were adopted to calculate the equivalent yaw moments for the vehicle stability in upper controllers. The linear quadratic regulator （LQR） method was utilized to optimize the distribution of the front and rear steering angles and the tire longitudinal forces in middle controllers. The sliding-mode-based slip controller in the lower layer was also designed to reallocate the wheel torques. Simulation results show that the control system may make full use of the adhesion potential of the tire under high speed and extreme conditions, realize the coordinated distribution of wheel torques and improve the steering stability of the vehicles. When the actuators fail, the system may reconstruct effectively and realize the reallocation of control inputs to improve the safety of the vehicles.

Dual-mode Coupling Drive Control for Electric Vehicles on a Bisectional Ramp

ZHANG Lipeng, DONG Chuangchuang, ZHANG Wei, PANG Zhaowen, ZHANG Silong, JIA Qikang

2018, 29(15):  1788-1795. 

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The pass ability improvement of electric vehicles on bisectional ramps were done based on the invented dual-mode coupling drive systems. The torque output characteristics of the dual-mode coupling drive systems on a bisectional pavements and the pass ability control programs were analyzed. Then， the judgment rules of the mode switching control triggers were established according to the thresholds of the drive wheels slip ratios. Aimed at the initiative to adjust the rotational speeds of the drive motors in the processes of changing modes， fuzzy-PID controllers were established. The predictive function controllers were established according to the reference angular displacement curves of the mode switching actuators. Finally， the torque output characteristics and the actual mode-switching control effectiveness of the dual-mode coupling drive system were verified by comparison with other driving modes with bench and real car tests. The results show that the torque output characteristics of the dual-mode coupling drive system are very much in line with the technical requirements of electric vehicles. The flexible mode switching control functions improve the vehicle pass ability greatly on the bisectional ramps.

Intelligent Control System Framework for Multi-Agent Based Electric Vehicle Chassises

YIN Guodong, ZHU Tong, REN Zuping, LI Guangmin, JIN Xianjian

2018, 29(15):  1796-1801,1817. 

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To solve the problems that flexibility and scalability limitations of the traditional integrated chassis control frameworks and the traditional vehicles chassis control system was not suitable for distributed in-wheel motors drive electric vehicles， an intelligent chassis dynamic control system framework was proposed based on multi-Agent for four-wheel independent driving electric vehicles. And the functions and interrelations of layers were analyzed. Taking direct yaw-moment control Agent of underlying control layer as an example， the controller Agent model was designed. In the co-simulation environment including MATLAB/Simulink and Carsim， simulation tests were conducted with the conditions of front wheel steering angle step input. Simulation results show that the controller Agent model may achieve the desired objectives of dynamic control and improve the performances of lateral handling stability effectively， which lays the foundation for the proposed control framework.

Distributed Decoupled Robust Control of Heterogeneous Vehicular Platoon

GAO Feng, WANG Xiaotong

2018, 29(15):  1802-1807. 

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Based on the distributed control structure and interaction topology modeled by graph theory， a decoupled robust control strategy was presented for a heterogeneous vehicular platoon to deal with the uncertainties of node dynamics. The dynamical behavior of node composed of vehicle dynamics and a lower-level controller was assumed to be covered by a multiplicative uncertainty model. Then to decouple the platoon system， which  was skillfully decomposed into a H∞ norm bounded uncertain part and a diagonal system by applying linear transformation and eigenvalue decomposition on communication topology. The requirements of robust stability， tracking ability and vehicular platoon stability were analyzed theoretically. Comparative bench tests with a non-robust controller and different communication topologies were conducted to demonstrate its robust stability， tracking ability and vehicular platoon.

Automated Modeling Method for Tracked Vehicle Hybrid Drive Systems

ZOU Yuan, WU Jinlong, TIAN Ye, SUN Fengchun

2018, 29(15):  1808-1817. 

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Tracked vehicle hybrid drive system is a kind of electromechanical transmission system and equipment. In order to improve the efficiency of system design and modeling， an automated modeling method was proposed for a series-parallel tracked vehicle hybrid drive systems. Based on the modeling of a power combining device and a power convergent device， the automated modeling principles were illustrated and the automated modeling rules and the screening conditions were further proposed. Then the final model equation eliminated intermediate quantity was derived. With the automated modeling method， some tracked vehicle hybrid drive systems were modeled in Simulink to validate the method. The automated modeling processes were programmed. And as an application demonstration for the automated modeling， optimal configuration seeking was described. The results show the method may build the model and screening the configuration automatically， which is a powerful method for rapid and automated modeling of tracked vehicle hybrid drive systems.

Comprehensive Gear Shift Schedule of a Two-speed PEV Powertrain for Low Energy Consumption

LI Congbo, CHEN Ruijie, LI Yue, SHAN Yashuai

2018, 29(15):  1818-1825,1839. 

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In order to coordinate the contradiction between the dynamic performance and the economic performance of PEVs， this paper proposed a comprehensive shift schedule based on a two-speed PEV powertrain. Firstly， the strategies of obtaining the torque for low energy consumption were presented under the economic performance mode. Then the dynamic shift schedule and the economy shift schedule for a two-speed powertrain were formulated. The optimization model of comprehensive shift schedule was established with the objectives of the acceleration time during 0~100 km/h and the energy consumption per unit mass. And then the model was solved by the crossover particle swarm optimization algorithm to obtain the shift schedule curves. Three kinds of shift schedule were compared and analysed by using MATLAB/Simulink platform. Results show that the comprehensive shift schedule for low energy consumption may balance the dynamic performance and the economic performance of PEVs.

Real-time Tire-road Longitudinal Adhesion Estimation Based on Exponential Sum Linear Parameterization

XIONG Zhe, GUO Xuexun, PEI Xiaofei, ZHANG Jie

2018, 29(15):  1826-1833. 

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The wheel dynamics modeling and FFRLS （forgetting factor recursive least-square） were utilized to develop a method of tire-road adhesion estimations in longitudinal braking conditions. The modeling object was an FWD （front wheel drive） EV（electric vehicle） equipped with an EHB（electro-hydraulic brake）. Firstly， a maximized regenerative brake distribution strategy was introduced. The regenerative brake wheels would tend to be locked before other wheels in heavy brake conditions. Secondly， a real-time adhesion estimation method was designed to lowering the risks of wheel locks. The linear parameterization of ES（exponential sum） was introduced to fit non-linear Burckhardt friction model， the on-line simulations and HiL（hardware-in-loop） tests were conducted. Results show that the proposed linear method may run in real-time， and has better estimation accuracy and convergence rate compared with linear Kiencke method.

Cell SOC Estimation of Battery Packs Based on Dual Time-Scale EKPF

LIU Zhengyu, TANG Wei, WANG Xuesong, LI Panchun

2018, 29(15):  1834-1839. 

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In order to accurately estimate the SOC of the battery packs， a enhance self correcting（ESC） model was established for the lithium battery packs， and then an average battery model and a SOC difference model for each battery were established according to the ESC model of the lithium battery. The dual-time-scale EKPF algorithm was used to estimate the average SOC of the batteries and the differential SOC of each cell， so as to obtain the SOC of each cell in the batteries. The SOC estimation experiments of 12 lithium battery series were carried out .The results show that the SOC estimation method based on the dual time-scale EKPF algorithm may achieve accurate estimate of the cell SOC. And it is proved that the dual-time-scale EKPE algorithm has higher estimation accuracy than that of the dual time-scale EKF algorithm and EKF algorithm.

Model-based Multi-scale Thermal Safety Design of Traction Battery Systems

CHEN Tianyu, FENG Xuning, OUYANG Minggao, LU Languang

2018, 29(15):  1840-1846,1874. 

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Aiming at the thermal safety problems of lithium-ion traction battery systems， from the viewpoints of battery material modification， battery cell design and battery system design， a model-based thermal safety design and development method for battery systems was proposed. The test methods of thermal stability of battery materials， thermal runaway characteristics of battery cells and thermal runaway propagation of battery systems were summarized. Based on the measured parameters of battery thermal safety characteristics， the model of chemical reaction kinetics for thermal runaway of batteries， the model for predicting temperature and pressure of thermal runaway of cells， and the model for thermal runaway propagation of battery packs were set up. The factors needed to be considered in these models were listed. Using the model for simulation analysis， the main factors affecting the thermal safety of the battery systems were obtained and the design of multi-scale thermal safety was guided.

Design and Optimization of Thermal Management Systems for Lithium-ion Battery Module Based on Electro-thermal Model

JIANG Shuisheng, HE Zhijian, WEN Hua

2018, 29(15):  1847-1853. 

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Because of the uneven heat generation in battery module， the temperature rose differently and the working performances decreased. Thus the heat generation mechanism would be studied so that the electro-thermal model might be established， then the regularities of current density and heat generation rate distribution in stacks might be got. Battery module was simulated at different discharge rates based on those regularities， and coolant velocity was calculated based on cooling requests（temperature was between 25 ℃ and 40 ℃， temperature difference was below 5 ℃） and thermophysical parameter， then the cooling system might be designed. Simulation results of battery modules of several cool plates of different thickness were studied in different discharge rates， a best thickness（0.5 mm） of cool plate is found. At last， the cooling system was optimized based on original simulation results， and the optimized cooling system has better temperature uniformity.

Driving Range Estimation for Electric Vehicles through Vehicles，Roads， and Human Information Fusion

GAO Jianping, GAO Xiaojie, XI Jianguo

2018, 29(15):  1854-1862. 

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Aiming at driving cycle and driving style influenced significantly on remaining range estimation， which resulted in the remaining range estimation difficulty， a estimate method was adopted，which combined driving cycle with driver’s driving style，to estimation the driving range of electric vehicles. The typical driving condition fragments were selected based on large sample and traffic characteristics of Zhengzhou， which through principal component analysis and fuzzy C-means clustering technique.Under MATLAB/Simulink，a model to identify driving patterns was established based on principal component analysis and learning vector quantization by the typical driving condition fragments and driving style fuzzy recognition model， the remaining range estimation were carried out， which adopted joint simulation method，and the results of remaining range estimation were optimized by Kalman filtering. The simulation analysis and hardware in the loop test results show that driving range estimation for electric vehicles through vehicles，roads， and human information fusion method， reduces the remaining range estimation errors， and confirmes the feasibility of the method at the same time.

A Lane Identification Method Based on Morphological Features

CAI Yingfeng, GAO Li, SUN Xiaoqiang, CHEN Long, WANG Hai

2018, 29(15):  1863-1868. 

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The existing lane detection algorithm mainly used edge information to extract lane features， and the algorithm that generated feature points through the contrast of adjacent pixels was easily affected by many external factors， and the detection results were easily disturbed， thus a new feature extraction algorithm was proposed. This algorithm improved the robustness of the algorithm in complex situations by calculating the tensor rotation of the gray structure in the region and selecting the largest changing trend pixel as the feature point. A new lane line feature extraction algorithm was used to extract feature points in interest areas， then feature points were selected， and Hough transform was used to fit them. After the lane lines were obtained ， the dashed line and the solid line were distinguished by the coordinate variances of the feature points. The algorithm was tested by driving pictures of about 15 500 frames in different time periods. The results show that the detection method may detect the lane line well under various environments， the correct rate under the sunny conditions is as 99.18%， the correct rate under the rainy conditions is as 97.19%， and the correct rate under the worn pavement conditions is as 94.72%，the correct rate under the night conditions is as 97.62%.

Vehicle Detections Based on YOLO_v2 in Real-time

LI Zhou, HUANG Miaohua,

2018, 29(15):  1869-1874. 

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In order to solve the problems of poor real-time detection and single acquisition information from vehicle-mounted camera， a real-time vehicle detection algorithm was proposed based on improved YOLO_v2 model. Based on the YOLO_v2 network structure， a vehicle detection model was established， which proved that the YOLO_v2 algorithm had high accuracy and good real-time performance in vehicle detections. And the YOLO_v2 algorithm was improved so that the improved one might perform multi-dimensional judgments on the vehicle-mounted video informations： judging whether there was a vehicle and the vehicle positions in the pictures， judging the relative positions to camera and the movement trend of the detected vehicles， judging the danger degree of the detected vehicles to the own vehicle. The experimental results show that the improved model achieves good detection effectiveness on vehicle-mounted video， solves the problems of low real-time vehicle detections in vehicle-mounted video， extends the traditional vision-based vehicle detections from single dimensional detections to multi-dimensional detections.

DCR and Applications Based on PSO-SVM Algorithm

SHI Qin, QIU Duoyang, WU Bing, LI Yiming, LIU Bingjiao

2018, 29(15):  1875-1883. 

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The random number method was used to extract the DCR training and text samples based on collecting 4 typical driving cycle data in real vehicle tests. Multivariate statistical theory was used to process the data and the PSO-SVM algorithm was proposed to conduct DCR. The influences on the on-line identification accuracy of recognition period and update period were analyzed. Finally， DCR was applied in plug-in hybrid electric vehicle energy management strategy. The simulation results show that comparing with the energy management strategy without DCR and the energy management strategy with DCR based on traditional SVM algorithm， the fuel economy of the energy management strategy with DCR based on PSO-SVM algorithm increases by 9.836% and 4.348% respectively， and the battery state of charge（SOC） changes more steady， it is beneficial to improve the system efficiency and prolong the battery lifes.

Obstacle Detection Algorithm for Driverless Vehicles Based on Four-layer Lidars

WANG Hai, ZHENG Zhengyang, CAI Yingfeng, CHEN Long

2018, 29(15):  1884-1889. 

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Aiming at the problems that the resolution capability of lidar scanning angle was not high enough， the remote point cloud was sparse and the target segmentation and clustering were not accurate， an obstacle detection algorithm was proposed based on four-layer lidars. After rasterization and filtering of raw radar data， clustering and segmentation of filtering results were performed. The clustering distance threshold was determined by the grid depth values， and the accurate clustering ranges were obtained by connecting the connected region marking algorithm. The matching accuracy of clustering was further improved by matching the movement status informations of adjacent obstacles. The experimental results show that the proposed algorithm， compared with existing segmentation clustering algorithms， may obtain the information of obstacles on road accurately and prevent the over-segmentation effectively.