Estimation Method of State-of-Charge For Lithium-ion Battery Used in Hybrid Electric Vehicles Based on Variable Structure Extended Kalman Filter

Since the main power source of hybrid electric vehicle（HEV） is supplied by the power battery,the predicted performance of power battery,especially the state-of-charge（SOC） estimation has attracted great attention in the area of HEV.However,the value of SOC estimation could not be greatly precise so that the running performance of HEV is greatly affected.A variable structure extended kalman filter（VSEKF）-based estimation method,which could be used to analyze the SOC of lithium-ion battery in the fixed driving condition,is presented.First,the general lower-order battery equivalent circuit model（GLM）,which includes column accumulation model,open circuit voltage model and the SOC output model,is established,and the off-line and online model parameters are calculated with hybrid pulse power characteristics（HPPC） test data.Next,a VSEKF estimation method of SOC,which integrates the ampere-hour（Ah） integration method and the extended Kalman filter（EKF） method,is executed with different adaptive weighting coefficients,which are determined according to the different values of open-circuit voltage obtained in the corresponding charging or discharging processes.According to the experimental analysis,the faster convergence speed and more accurate simulating results could be obtained using the VSEKF method in the running performance of HEV.The error rate of SOC estimation with the VSEKF method is focused in the range of 5% to 10% comparing with the range of 20% to 30% using the EKF method and the Ah integration method.In Summary,the accuracy of the SOC estimation in the lithium-ion battery cell and the pack of lithium-ion battery system,which is obtained utilizing the VSEKF method has been significantly improved comparing with the Ah integration method and the EKF method.The VSEKF method utilizing in the SOC estimation in the lithium-ion pack of HEV can be widely used in practical driving conditions.

On-Line Structural Breaks Estimation for Non-stationary Time Series Models

Non-stationary time series could be divided into piecewise stationary stochastic signal. However, the number and locations of breakpoints, as well as the approximation function of the respective segment signal are unknown. To solve this problem, a novel on-line structural breaks estimation algorithm based on piecewise autoregressive processes is proposed. In order to find the "best" combination of the number, lengths, and orders of the piecewise autoregressive (AR) processes, the Akaikes Information Criterion (AIC) and Yule-Walker equations are applied to estimate an AR model fit to the data. Numerical results demonstrate that the proposed estimation algorithm is suitable for different data series. Furthermore, the algorithm is used in a clinical study of electroencephalogram (EEG) with satisfactory results, and the ability to deal with real-time data is the most outstanding characteristic of on-line structural breaks estimation algorithm proposed.

Compressed sensing-based structured joint channel estimation in a multi-user massive MIMO system

Acquisition of accurate channel state information （CSI） at transmitters results in a huge pilot overhead in massive multiple input multiple output （MIMO） systems due to the large number of antennas in the base station （BS）. To reduce the overwhelming pilot overhead in such systems, a structured joint channel estimation scheme employing compressed sensing （CS） theory is proposed. Specifically, the channel sparsity in the angular domain due to the practical scattering environment is analyzed, where common sparsity and individual sparsity structures among geographically neighboring users exist in multi-user massive MIMO systems. Then, by equipping each user with multiple antennas, the pilot overhead can be alleviated in the framework of CS and the channel estimation quality can be improved. Moreover, a structured joint matching pursuit （SJMP） algorithm at the BS is proposed to jointly estimate the channel of users with reduced pilot overhead. Furthermore, the probability upper bound of common support recovery and the upper bound of channel estimation quality using the proposed SJMP algorithm are derived. Simulation results demonstrate that the proposed SJMP algorithm can achieve a higher system performance than those of existing algorithms in terms of pilot overhead and achievable rate.

AN ESTIMATE OF THE EFFECTS OF LARGE SCALE STRUCTURES ON THE TURBULENT TRANSPORT PROCESSES NEAR WALL

Based on the three-term decomposition model for turbulent flows, the fundamental equations for quasi-periodic motions are obtained, and the approximate analytical solutions of these second-order nonlinear partial differential equations are derived by using the match method. The effects on the mo- mentum, heat and mass transport processes in the wall turbulent flows can be estimated approximately.

Geothermal data analysis at the high-temperature hydrothermal area in Western Sichuan

The western Sichuan hydrothermal area is located at the northeastern margin of the eastern syntaxis of the Qinghai-Tibet Plateau, which is also the eastern end of the Mediterranean-Himalayan geothermal activity zone. There are 248 warm or hot springs in this area, and 11 have temperatures beyond the local boiling temperature. Most of these hot springs are distributed along the Jinshajiang, Dege-Xiangcheng, Ganzi-Litang, and Xianshuihe faults, forming a NW-SE hydrothermal belt. A geothermal analysis of this high-temperature hydrothermal area is an important basis for understanding the deep geodynamic process of the eastern syntaxis of the Qinghai-Tibet Plateau. In addition, this study offers an a priori view to utilize geothermal resources, which is important in both scientific research and application. We use gravity, magnetic, seismic, and helium isotope data to analyze the crust-mantle heat flow ratio and deep geothermal structure. The results show that the background terrestrial heat flow descends from southwest to northeast. The crustal heat ratio is not more than 60%. The high temperature hydrothermal active is related to crustal dynamics processes. Along the Batang-Litang-Kangding line, the Moho depth increases eastward, which is consistent with the changing Qc/Qm(crustal/mantle heat flow) ratio trend. The geoid in the hydrothermal zone is 4–6 km higher than the surroundings, forming a local "platform". The NW-SE striking local tensile stress zone and uplift structure in the upper and middle crust corresponds with the surface hydrothermal active zone. There is an average Curie Point Depth(CPD) of 19.5–22.5 km in Batang, Litang, and Kangding. The local shear-wave(S-wave) velocity is relatively low in the middle and lower crust. The S-wave shows a low velocity trap(Vs<3.2 km s.1) at 15–30 km, which is considered a high-temperature partial melting magma, the crustal source of the hydrothermal active zone. We conclude that the hydrothermal system in this area can be divided into Batang-type and Kangding-type, both of which rely on a crustal heating cycle of atmospheric precipitation and surface water along the fracture zone. The heat is derived from the middle and lower crust: groundwater penetrates the deep faults bringing geothermal energy back to the surface and forming high-temperature springs.