To make certain the lithium battery's terminal limited discharge voltage and internal resistance in different load, four 3.2V/60 Ah lithium batteries are put in series to form battery pack in tests. The lithiu...
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ISBN:
(纸本)9781424479573
To make certain the lithium battery's terminal limited discharge voltage and internal resistance in different load, four 3.2V/60 Ah lithium batteries are put in series to form battery pack in tests. The lithium battery pack terminal voltage, current and overall internal resistance were recorded with the discharge time. By analyze datas from the tests with MATLAB, the lithium battery pack capacity, energy consumed by the load and internal resistance are figured out, lithium battery pack t-U, t-I, t-△U/△t and t-r0 graphs are drawn. From the graphs, we can draw that the limited discharge voltage of a single lithium battery is about 2.75V, the internal resistance of a single lithium battery is about 0.75mΩ, the lithium battery pack current and the voltage change trends are the same when the load keeps changeless, the higher load the less capacity lithium battery pack can release, the energy comsumed by internal resistance to the energy that lithium battery release is higher as the load increase. All the conclutions can do good to develop battery management system.
This paper describes a method of mobile robot simultaneous localization and mapping (SLAM) based on laser range finder in unstructured environments. Considering drawbacks of the traditional iterative closest point (IC...
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This paper describes a method of mobile robot simultaneous localization and mapping (SLAM) based on laser range finder in unstructured environments. Considering drawbacks of the traditional iterative closest point (ICP) algorithm, matching laser range scans gets into local extrema when severe occlusions occur, the iterative dual closest point based on clustering (IDCP BoC) algorithm is proposed. Scan data are filtered and divided into clusters firstly, and then a procedure of reducing of data is conducted. The closest point (CP) rule is modified and dual closest point (DCP) rule is advanced when choosing the closest points. The reduced data is used for iterative computation before the error of two consecutive iterations' residual errors less than a preset threshold to speed up the algorithm, after that the data which is not reduced is used to guarantee the accuracy. Experimental results show that the method improves the accuracy of localization and mapping.
Analysing the cotton picker in current situation of China, this paper proposed a new design of Intelligent Cotton Picking Robot (ICPR) based on machine vision including the motion control subsystem and machine vision ...
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Analysing the cotton picker in current situation of China, this paper proposed a new design of Intelligent Cotton Picking Robot (ICPR) based on machine vision including the motion control subsystem and machine vision subsystem. The former adopts the YASKAWA MP2100 as the core, which can control the robot of 4-DOF and X-axis. The latter based on the interface module of SEED-VPM642 with 2-CCD cameras, can get an efficient and precise recognition. The identification of mature cotton is one of the critical tasks in this robotic application. According to the statistic experiments and analysis, an optimized segmentation algorithm based on chromatic aberration is studied. The results demonstrate that the method for cotton recognition is well done and the increased pace helps improve the speed of the processing.
Based on analysis of cutting force, this paper studies the method for modeling and compensation of cutting force induced error. According to the relation between feed servo motor current and cutting force, online moni...
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Based on analysis of cutting force, this paper studies the method for modeling and compensation of cutting force induced error. According to the relation between feed servo motor current and cutting force, online monitoring of cutting force is realized by measuring the motor current. For the delay of current signal to cutting force, a reasoning method with artificial neural network is proposed to predict correctly and monitor the cutting force online. The cutting force induced error is obtained by subtracting the geometric error from the total error which is measured with a laser interferometer within the working volume. According to the multi-body system theory and the back-propagation neural network, cutting force induced error model is developed. In addition, a real-time compensation system for cutting force induced error is built up with the VC++ softwareplatform. The validity of the error model and reliability of the compensation method is examined by milling experiments. The results demonstrate that the developed approach reduces the cutting force error markedly, and the method for modeling and compensation is of great important to precision manufacturing.
The three-layer modified fast BP neural network (MFBPNN) is used to solve the converse kinematics problems of five-freedom multi-joint robot. The sample vectors of forward kinematics are used to train the weights of M...
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The three-layer modified fast BP neural network (MFBPNN) is used to solve the converse kinematics problems of five-freedom multi-joint robot. The sample vectors of forward kinematics are used to train the weights of MFBPNN off-line. Then the generalization characteristic of artificial neural network (ANN) is fully utilized to accomplish the nonlinear map of the end-effector position and gesture to all joint rotating angles. Simulation results demonstrate that the calculation precision and the velocity satisfy the demands of the real-time control. The absolute angle error is less than 0.005°, and the method can be applied to the situation of the robot route plan.
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