This paper presents a lithium-ion battery aging study in which pouch cells comprising a LiCoO 2 /LiNi 0.8 Co 0.15 Al 0.05 O 2 blended cathode and a graphite anode are examined. The study focuses on the impact of temperature and discharge rate on the cycle life of the tested cells. Compared to the aging behavior of other lithium-ion cells in the literature, the cells tested here are less sensitive to the discharge rate but more vulnerable to low temperature cycling. The vulnerability to low temperature mainly comes from cathode degradation, especially of the LiCoO 2 component. This is identified by electrochemical impedance spectroscopy, differential voltage analysis and incremental capacity analysis. The cells are able to achieve 3000-5000 cycles before reaching a capacity fade of 20%, also at higher discharge rates up to 5C. All in all, the high discharge rate capability could be a general advantage of pouch cells due to less mechanical and thermal stress in their geometry. Furthermore, more attention should be paid to the cathode health in low temperature applications of lithium-ion cells containing layered oxides. This paper focuses mainly on non-invasive aging detection methods for lithium-ion cells. Post-mortem results will be published in a following paper.
Skid-steering mobile robots are widely used because of their simple mechanism and robustness. However, due to the complex wheel-ground interactions and the kinematic constraints, it is a challenge to understand the kinematics and dynamics of such a robotic platform. In this paper, we develop an analysis and experimental kinematic scheme for a skid-steering wheeled vehicle based-on a laser scanner sensor. The kinematics model is established based on the boundedness of the instantaneous centers of rotation (ICR) of treads on the 2D motion plane. The kinematic parameters (the ICR coefficient χ, the path curvature variable λ and robot speed v), including the effect of vehicle dynamics, are introduced to describe the kinematics model. Then, an exact but costly dynamic model is used and the simulation of this model’s stationary response for the vehicle shows a qualitative relationship for the specified parameters χ and λ. Moreover, the parameters of the kinematic model are determined based-on a laser scanner localization experimental analysis method with a skid-steering robotic platform, Pioneer P3-AT. The relationship between the ICR coefficient χ and two physical factors is studied, i.e., the radius of the path curvature λ and the robot speed v. An empirical function-based relationship between the ICR coefficient of the robot and the path parameters is derived. To validate the obtained results, it is empirically demonstrated that the proposed kinematics model significantly improves the dead-reckoning performance of this skid–steering robot.
In order to detect X-corner (or X-point) features more accurately and apace, this article presents a novel and fast detection method based on block-by-block search strategy. Unlike general pixel-by-pixel searching method, the sampling window is first moved along the image block-by-block to find the X-corner candidates rapidly keeping in view the fourstep and min-step-distance constraints. During the motion, some overlap is kept between the adjacent sampling windows in order to ensure that all X-corners could have a chance to reside inside, avoiding the possibility of that some Xcorners may locate on the edge. Moreover, labeling technology is adopted to prevent duplicate candidates. After the collection of X-corner candidates, the neighborhood variance and centrosymmetry constraints are used to exclude outliers, and the intersection lines is calculated as the sub-pixel position of true X-corner. The experimental results using synthetic and real images show that the presented method approximately takes just about 13 ms to detect 52 X-corners in an image size of 1024 3 768 on a computer having Intel Core i3 CPU at 3.6 GHz and 4GB RAM. The proposed method has faster detection speed compared with the latest methods such as ChESS, SC, and Micron Tracker system while possessing the same or higher detection precision.
At present, most research on the fairness of recommender systems is conducted either from the perspective of customers or from the perspective of product (or service) providers. However, such a practice ignores the fact that when fairness is guaranteed to one side, the fairness and rights of the other side are likely to reduce. In this paper, we consider recommendation scenarios from the perspective of two sides (customers and providers). From the perspective of providers, we consider the fairness of the providers' exposure in recommender system. For customers, we consider the fairness of the reduced quality of recommendation results due to the introduction of fairness measures. We theoretically analyzed the relationship between recommendation quality, customers fairness, and provider fairness, and design a two-sided fairness-aware recommendation model (TFROM) for both customers and providers. Specifically, we design two versions of TFROM for offline and online recommendation. The effectiveness of the model is verified on three real-world data sets. The experimental results show that TFROM provides better two-sided fairness while still maintaining a higher level of personalization than the baseline algorithms.
In this paper, the data fusion algorithm for position estimation of the wireless sensor networks is investigated. A hybrid position scheme with both radio based ranging measurement and time-based ranging measurement is proposed. The position estimation performances of RSSI and TOF are compared and analyzed. A novel data fusion algorithm along with traditional Kalman filter is advanced to improve the positioning and tracking accuracy. Several simulation experiments are carried out, which show the validity of the presented algorithm.
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