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The paper utilizes a novel battery model based on the electrical features of LiFePO4 battery, because Kalman filter algorithm(KF) is largely dependent on system model. Measurements of battery state are easily disturbed by colored noise which is high relevance in working condition, and the paper studies that the system noise satisfy one-order AR model. The paper proposes an adaptive extended Kalman...
State-of-charge (SOC) estimation methods based on battery model rely heavily on the accuracy of model parameters. And these parameters could vary with environment and the types of batteries. Online battery modeling methods can improve the robustness of SOC estimation algorithms through updating model constantly with real-time data. These methods have far more profound significance on algorithm adaptability...
State of charge is a significant indicator with respect to the remaining capacity for the lithium-ion battery. Nonetheless, strong nonlinearity and time-varying attributes resulting from the complicated electrochemical reactions incur the tremendous difficulty to acquire the accurate state directly. To address the above problems, a novel estimation method based on unscented Kalman filter and dual-filters...
Forty years of cross-disciplinary academic and industrial research & development work on radar tracking systems is surveyed, starting from the former implementations based on the α — β, the Kalman filter up to the modern implementations based on random set filters.
This paper provides a comparative evaluation of phasor estimation signal processing tools, namely the least square estimator and the linear Kalman filter. Comparative investigations are carried out using simulated signals for a power grid voltage sag disturbance. For both techniques, the fundamental frequency is assumed known, hence the estimated phasor parameters are amplitude and initial phase....
This paper presents an Unscented Kalman filter (UKF) based algorithm for estimating available bandwidth in a space Disruption-Tolerant Network (DTN) link. In the proposed algorithm, an UKF model is proposed for accurately tracking available bandwidth of bundle delivery over a space link. In particular, the proposed UKF will iteratively filter a serial of noised measurements on successive time intervals,...
This paper studies a selection of estimation schemes for tracking problems where sensors measure range and Doppler while no directional measurements are provided. The selected estimators are relatives of the Kalman filter where either the state propagation equation or the measurement equation is non-linear. Known schemes are compared with a new filter operating in Cartesian state space. The new filter...
This paper presents the design of Unscented Kalman Filter (UKF) for estimation of state space variables of permanent magnet synchronous machine (PMSM). The UKF is shown together with the field oriented speed control. At first, the position and the speed of PMSM are measured, and UKF is used only for a load torque estimation. It is indicated how differences in sampling time of the speed and the current...
The paper describes and compares some approaches to the use of measurement results for control using the classical feedback principle. The application of a linear control law based on the state vector estimates obtained with the use of the Kalman filter and the minimax filter is described. There are methods for control quality improving by means of the preliminary processing of measurements and another...
Distributed estimation has been an active research area since the late 1970's, starting with decentralized filtering and estimation for control of large scale systems. Early research focused on optimal fusion to reconstruct the best global estimate by de-correlating the local estimates to avoid double counting of information. This approach was extended to distributed estimation for general sensor...
This paper is motivated by the problem of two adversarial networked teams that collect information about each other and make decisions based on this information. This problem has applications in network security, economic decision making, and robotic soccer. From the perspective of one team, the quality of decision making can be improved with better methods of aggregating measurements of the other...
With the increase of state dimension, the calculation of UKF algorithm increases rapidly, and UKF is more sensitive to model error, and it is not suitable for the system model with noise as non-Gaussian distribution. Aiming at this problem, this paper proposes a robust model predictive Unscented Kalman filter based on the study of robust estimation, model predictive filtering and UKF. The algorithm...
We have previously proposed a novel parameter identification method for the Li-ion battery equivalent circuit model (ECM) considering the electrochemical properties, with which a second order ECM resistances/capacitances values can be obtained from electrochemical parameters. In this paper, we apply this physics-based ECM with Kalman filter for cell SOC estimation. To implement the Kalman filter to...
This paper presents an extended BLUE filter with Pitot tube and windspeed measurements. Though widely used in aviation, Pitot tube is ignored by scholars because it only measures the speed of an aircraft relative to the air. Investigation shows the linear combination of Pitot tube and windspeed measurements can yield aircraft velocity estimation to improve performance. After a thorough analysis of...
The accurate estimation of state of charge (SOC) is crucial for the management of the power battery for electric vehicles. The electric vehicle often encounters data mutation when it is actually running. In this paper, a new adaptive fading extended Kalman filter (AFEKF) is applied in the SOC estimation of Lithium-ion battery. AFEKF can reduce the influence of data mutation through the adaptive iterating...
Knowing the wind speed is an important factor that includes several scientific areas. For the types of existing anemometers, the ultrasonic model is what can be used in most applications. As part of the necessary calculus for wind speed acquisition, it is needed to find the correct ultrasonic echo emitted that has been corrupted by the environmental conditions imposed on it, and is the bigger challenge...
In this paper, the problem of sequentially fusion filtering for multi-sensor systems with bounded noise energy is addressed. According to different performance index functions, three different methods of sequential HTC fusion filtering are proposed. Firstly, a sequential H∞ fusion filter is given by the intuitivism apprehension of the sequential fusion strategy. Then, two other sequential HOT fusion...
Big GPS data from the moving vehicles allow understanding the transportation systems in more details and at a vehicle level. While only depending on the trajectory and speed data from probe vehicles cannot estimate the traffic states (vehicle densities etc.) in real-time with the classical filtering methods, such as particular filtering (PF) and extended Kalman filtering (EKF), because the boundary...
Based on the decentralized computing platform, a decentralized Kalman filter with state constraints is presented in this paper. The decentralized sensing architecture takes the form of a network of transputer-based sensor nodes, each with its own processing facility. So it does not require any central processor, central communication facility or common clock. Based on that, the starting point is an...
A real-time posture estimation system by interacting multiple model (IMM) based unscented Kalman filters (UKFs) is presented in this paper. The system is developed on an inertial measurement unit (IMU) development board which is integrated with multi-sensors, microcontroller, and WIFI module, aiming at obtaining high accuracy posture estimation. In order to reduce the overall estimation error of the...
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