Combined Estimation of Vehicle Dynamic State and Inertial Parameter for Electric Vehicles Based on Dual Central Difference Kalman Filter Method

Distributed drive electric vehicles(DDEVs)possess great advantages in the viewpoint of fuel consumption,environment protection and traffic mobility.Whereas the effects of inertial parameter variation in DDEV control system become much more pronounced due to the drastic reduction of vehicle weights and body size,and inertial parameter has seldom been tackled and systematically estimated.This paper presents a dual central difference Kalman filter(DCDKF)where two Kalman filters run in parallel to simultaneously estimate vehicle different dynamic states and inertial parameters,such as vehicle sideslip angle,vehicle mass,vehicle yaw moment of inertia,the distance from the front axle to centre of gravity.The proposed estimation method only integrates and utilizes real-time measurements of hub torque information and other in-vehicle sensors from standard DDEVs.The four-wheel nonlinear vehicle dynamics estimation model considering payload variations,Pacejka tire model,wheel and motor dynamics model is developed,the observability of the DCDKF observer is analysed and derived via Lie derivative and differential geometry theory.To address system nonlinearities in vehicle dynamics estimation,the DCDKF and dual extended Kalman filter(DEKF)are also investigated and compared.Simulation with various maneuvers are carried out to verify the effectiveness of the proposed method using Matlab/Simulink-CarsimR.The results show that the proposed DCDKF method can effectively estimate vehicle dynamic states and inertial parameters despite the existence of payload variations and variable driving conditions.This research provides a boot-strapping procedure which can performs optimal estimation to estimate simultaneously vehicle system state and inertial parameter with high accuracy and real-time ability.

Adaptive unscented Kalman filter for parameter and state estimation of nonlinear high-speed objects

An adaptive unscented Kalman filter （AUKF） and an augmented state method are employed to estimate the timevarying parameters and states of a kind of nonlinear high-speed objects. A strong tracking filter is employed to improve the tracking ability and robustness of unscented Kalman filter （UKF） when the process noise is inaccuracy, and wavelet transform is used to improve the estimate accuracy by the variance of measurement noise. An augmented square-root framework is utilized to improve the numerical stability and accuracy of UKF. Monte Carlo simulations and applications in the rapid trajectory estimation of hypersonic artillery shells confirm the effectiveness of the proposed method.

Estimation and Prediction of Bioconcentration Factors of Nonionic Organic Chemicals in Fish by Electrotopological State Indices and Structural Parameter

Based on the characteristics of atom types, Hall＇s electrotopological state indices （En） are calculated for 165 nonionic organic compounds. On the basis of the characteristics of substituent and conjugated matrix, a novel molecular structure parameter （G） is defined and calculated for 165 molecules in this paper. En and G show good structural selectivity for organic molecules. G, a satisfactory relationship between bioconcentration factor （BCF） and En, is expressed as： 1gBCF = -0.283 ＋ 1.246G ＋ 0.079E42 ＋ 0.351E9- 0.063E17 （n＇ = 122, R = 0.967, F = 425.636, s = 0.394）, which could provide estimation and prediction for the lgBCF of nonionic organic chemicals. Furthermore, the model is examined to validate overall robustness with Jackknife tests, and the independent variables in model do not exist cross correlation with VIF. All these regression results show that the new parameter G and electrotopological state index have good rationality and efficiency. It is concluded that the En and G will be used widely in quantitative structure-property/activity relationship （QSPR/QSAR） research.

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed timevarying delays and Markovian jumping parameters.The addressed neural networks have a finite number of modes,and the modes may jump from one to another according to a Markov process.By construction of a suitable Lyapunov-Krasovskii functional,a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square.The criterion is formulated in terms of a set of linear matrix inequalities（LMIs）,which can be checked efficiently by use of some standard numerical packages.

Effects of Solid-State Reaction Synthesis Processing Parameters on Thermoelectric Properties of Mg_2Si

The Mg_(2)Si-matrix thermoelectric material was synthesized by low temperature solid-state reaction.This paper studies the effects of holding time and reaction temperature on the particle size and the properties of the material,and also studies effects of doping elemental Sb,Te and their doping seqence on the properties of the material.The result shows that excessively high temperature and elongated holding time of solid-state reaction are harmful,there is a range of particle size to ensure optimum properties and the doping sequence of Sb or Te without influencing the properties.

Parameter identification and state-of-charge estimation approach for enhanced lithium–ion battery equivalent circuit model considering influence of ambient temperatures

It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge(SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model(ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium-ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter(EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization(HPPC) and the standard US06 driving cycles(US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.

A four parameter cubic equation of state with temperature dependent covolume parameter

A four-parameter, Ghoderao–Dalvi–Narayan 2 cubic equation of state(GDN2 CEOS), is presented which incorporates the following: 1. The experimental value of the critical compressibility factor has been used as a fixed input parameter for calculations;2. All the parameters(a, b, c, d) of CEOS are temperature dependent functions in the subcritical region and are temperature independent functions in the supercritical region and;3. A new α function is introduced with two compound specific parameters which are estimated by matching saturated vapor pressure at two fixed temperature points Tr= 0.5, 0.7. Our formalism enables us to cast three of the four parameters of the CEOS as a function of the remaining parameter. The proposed CEOS is used to predict properties of 334 pure compounds, including saturated vapor pressure and liquid density, compressed liquid density, heat capacities at the constant pressure and volume, enthalpy of vaporization, sound velocity. To calculate thermodynamic properties of a pure compound, the present CEOS require the critical temperature, the critical pressure, the Pitzer’s acentric factor, the critical compressibility factor, and two parameters of the alpha function. The saturated liquid density predictions for pure fluids are very accurate when compared with GDN1(Ghoderao–Dalvi–Narayan 1),MPR(Modified Peng–Robinson), and PT(Patel–Teja) equations of state. Unlike MPR EOS, the proposed temperature dependent covolume parameter b in the present work satisfies all the constraints mentioned in the literature to avoid thermodynamic inconsistencies at the extreme temperature and pressure. Using van der Waals one-fluid mixing rule, the present CEOS is further used to predict bubble pressure and the vapor mole fraction of binary mixtures.

A Two－Stage Approach of Integrated Parameter Identification and State Estimation

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Ground-state energy of beryllium atom with parameter perturbation method

We present a perturbation study of the ground-state energy of the beryllium atom by incorporating double parameters in the atom＇s Hamiltonian. The eigenvalue of the Hamiltonian is then solved with a double-fold perturbation scheme,where the spin-spin interaction of electrons from different shells of the atom is also considered. Calculations show that the obtained ground-state energy is in satisfactory agreement with experiment. It is found that the Coulomb repulsion of the inner-shell electrons enhances the effective nuclear charge seen by the outer-shell electrons, and the shielding effect of the outer-shell electrons to the nucleus is also notable compared with that of the inner-shell electrons.

No Degeneracy of the Ground State for the Impact Parameter Model

A time dependent Hamiltonian associated to the impact parameter model for the scattering of a light particle and two heavy ones is considered. Existence and non degeneracy of the ground state is shown.

A Survey on Neuropsychological State, Oxidative Stress and Hematological Parameters in Coke Oven Workers

Coke oven factories are one of the main emitting sources of polycyclic aromatic hydrocarbons (PAH)s which have been identified as highly carcinogenic chemicals by IARC. Induction of oxidative stress and following disrupting pathways has been repeatedly reported in subjects exposed to PAHs. This study was performed to monitor the oxidative stress markers, hematological and biochemical parameters, and psychological states in coke oven workers. 100 male subjects were included in this comparative cross-sectional study. At first 50 male workers who were 22 - 63 and worked in the steel factory located in South-East of Iran were contained. Control subjects were chosen from Esfahan, in the factory’s neighborhood, consisting of 50 office workers without any background of occupational exposure to metals. The blood levels of hematological factors and oxidative stress were measured. In order to compare data, two-sample t test was applied. In order to measure the correlation between variables, Pearson correlation coefficient was applied. The mean level of total antioxidant capacity, hemoglobin (Hb), mean corpuscular hemoglobin concentration (MCHC), and hematocrit were significantly lower in the workers in association with increased lipid per oxidation (LPO). A positive correlation existed between work history, hyper thyroids (r2 = 0.288, p = 0.01), and endocrine disorders (r2 = 0.309, p = 0.028). Occupational exposure of coke oven workers to PAHs can induce oxidative stress and consequent metabolic and neuropsychological disorders. When workers take daily shower and use protective tools, absorption of toxic elements would decrease so that reaching them to the body can be suitably limited.

Superconducting state parameters of AgxZn1-x and AgxAl1-x binary alloys superconductors

A well-known pseudopotential is used to investigate the superconducting state parameters （SSP）, viz., electronphonon coupling strength, Coulomb pseudopotential, transition temperature, isotope effect exponent and effective interaction strength for AgxZn1-x and AgxAl1-x binary alloys theoretically for the first time. We have incorporated here five different types of the local field correction functions to show the effect of exchange and correlation on the aforesaid properties. Very strong influence of various exchange and correlation functions is concluded from the present study. Comparison with others such experimental values is encouraging, which confirms applicability of the model potential in explaining the superconducting state parameters of binary mixture.

Minimum norm method of analyzing ill-conditioned state of design matrix in estimation of parameters

The method of condition number is commonly used to diagnose a normal matrix N whether it is ill conditioned state or not. For its shortcoming, a method to measure multi collinearity of a matrix was put forward. The method is that implement Gram Schmidt orthogonalizing process to column vectors of a design matrix A (α l ), then calculate the norms of every vector before and after orthogonalization process and their corresponding ratio, and use the minimum ratio among the group of ratios to measure the multi collinearity of A. According to the corresponding relationship between the multi collinearity and the ill conditioned state of a matrix, the method also studies and offers reference indexes weighing the ill conditioned state of a matrix based on the relative norm. The remarkable characteristics of the method are that the measure of multi collinearity has idiographic geometry meaning and clear lower and upper limit, the size of the measure reflects the multi collinearity of column vectors objectively. It is convenient to study the reason that results in the matrix being multi collinearity and to put forward solving plan according to the method which is summarized as the method of minimum norm and abbreviated as F method.

Mass-Spring-Damper Model with Steady State Parameters for Predicting the Movement of Liquid Column and Temperature Oscillation in Loop Heat Pipe

In order to investigate the mechanism of the temperature oscillation in loop heat pipes,this paper investigated the movement of the phase interface as the changed input power by a mass-spring-damper model.The model was solved with MATLAB and was used to explain the high-frequency and low-amplitude temperature oscillation.Temperature variation with the input power from 20 W to 75 W was investigated based on a LHP prototype in a literature.The model agreed well with the experimental data in the literature.The simulation results suggested that the movement of the liquid column was caused by the fluctuation of pressure difference applied on the liquid column and the stiffness coefficients of the vapor springs increasing with the input power.According to parameter analyses,the temperature oscillation at the outlet of the condenser can be weakened by increasing the mass of the liquid column and keeping the temperature at the outlet of the condenser steady.

Soft Sensor for Inputs and Parameters Using Nonlinear Singular State Observer in Chemical Processes

Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.

Interval finite difference method for steady-state temperature field prediction with interval parameters

A new numerical technique named interval finite difference method is proposed for the steady-state temperature field prediction with uncertainties in both physical parameters and boundary conditions. Interval variables are used to quantitatively describe the uncertain parameters with limited information. Based on different Taylor and Neumann series, two kinds of parameter perturbation methods are presented to approximately yield the ranges of the uncertain temperature field. By comparing the results with traditional Monte Carlo simulation, a numerical example is given to demonstrate the feasibility and effectiveness of the proposed method for solving steady-state heat conduction problem with uncertain-but-bounded parameters.

Alternation in F-wave parameters of median nerve from unaffected extremity in stroke patients with hemiplegia under dynamic state

BACKGROUND: For many years, the extremities of stroke patients are divided into affected side and unaffected side according to clinical symptoms and body signs. Moreover, previous rehabilitation function training is developed simply aiming to the dysfunction manifested by unaffected extremity. Problems of unaffected extremity are always ignored, such as left- and right- side connection dysfunction, abnormal muscular tension of unaffected side and so on. OBJECTIVE: To observe neurophysiological change characteristics of unaffected extremity of stroke patients with hemiplegia by electromyographical method. DESIGN: Case-control observation. SETTING: First Hospital, Jilin University. PARTICIPANTS: Eighty stroke patients with hemiplegia confirmed by skull CT or MRI, who firstly hospitalized in the Department of Neurology, First Hospital, Jilin University between July 2004 and March 2005, were retrieved. They were scored > 8 points in Glasgow Coma Scale and had stable vital sign. Nineteen normal persons who received healthy examination in the clinic were involved in normal control group. Following the classification criteria of Brunnstrom's Recovery Stages of Stroke (BRSS), 80 stroke patients with hemiplegia were assigned into 3 groups: BRSS Ⅰ-Ⅱ group (n =36), BRSS Ⅲ-Ⅳ group (n =23) and BRSSⅤ-Ⅵ (n =21). METHODS: F-wave parameters of median nerve of unaffected extremity were detected by electromyographical technique. The recording electrode (muscular belly of abductor pollicis brevis) and reference electrode (first finger bone) were connected with grounding electrode. Stimulating electrode was placed in the median part of wrist joint with stimulation intensity of 130% that of threshold stimulation, stimulation frequency of 2 Hz, current pulse width of 0.2 ms, time course of 5 ms and sensitivity of 2 mV. The F-wave of median nerve of affected extremity under the resting stage (static status) and that of unaffected extremity under the maximum resistant contracted state were detected in order. The amplitude and appearance percentage of F wave were recorded. MAIN OUTCOME MEASURES: Comparison of F-wave parameters of median nerve between the unaffected extremity of stroke patients with hemiplegia and the extremity of control subjects under different status. RESULTS: All the patients accomplished the detection, and all of them participated in the final analysis. ①Under dynamic status, the amplitude and appearance percentage of F wave of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group were significantly higher than those in the normal control group, respectively[(0.803 9±0.157 3) mV vs. (0.406 7±0.170 3) mV; (0.856 1±0.266 8)% vs. (0.650 0±0.197 6)%, P < 0.05]. Under static status, there were no significant differences in F-wave parameters of median nerve in the unaffected extremity of patients between BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group (P > 0.05). ②F-wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅰ-Ⅱ group and BRSS Ⅴ-Ⅵ group under dynamic statewere higher than those under static status, without significant difference (P > 0.05), while the amplitude and appearance percentage of F wave of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group under dynamic statewere significantly higher than those under static state[(0.803 9±0.157 3) mV vs. (0.391 7±0.131 6) mV; (0.856 1±0.266 8 )% vs.(0.639 1 ±0.259 4)%,P < 0.05]. ③ There was no significant difference in F wave parameters among groups under static state(P > 0.05). However, under dynamic status, the amplitude and appearance percentage of F wave parameters of median nerve of unaffected extremity of patients in BRSS Ⅲ-Ⅳ group [(0.803 9±0.157 3) mV,(0.856 1±0.266 8)%] were significantly lower than those in the other two groups [(0.395 1±0.148 8),(0.437 1±0.157 6) mV;(0.612 5±0.232 8)%,(0.657 1±0.232 5)%,P < 0.05]. CONCLUSION: With the development of disease condition and the increase of muscular tension at anesthetic side, combination motor of affected extremity is caused following movement and muscular tension enhances to non-anesthetic-side. Therefore, F-wave parameters increase under dynamic status.

Estimating Hydrogeological Parameters in Covered Carbonate Rocks Using a Discrete-State Compartment Model and Environmental Tritium

Nowadays, isotope environmental technique tends to be used as a reconnaissance tool , both qualitative and quantitative, to calculate the aquifer parameters particularly in carbonate rock aquifers. But, the heterogeneous flow is still problematic when Lumped parameter Models are usually used to calculate the residence times and hydraulic parameters. However, Discrete State Compartment Model can provide a powerful model to heterogeneous medium. One such study was carried on in Dazha valley, where the environmental tritium was used as a tracer for determining hydrogeological parameters based on a discrete state compartment

Development of nonlinear cross-anisotropic model for sands based on state parameter

Numerous experimental studies reveal that the mechanical and deformational behaviors of sands are dependent on the combined effect of void ratio and stress. To predict this complex behavior of sands, a hypo-elastic model is developed based on the cross-anisotropic elasticity model, which involves four parameters: bulk module, tangent Young's module, volume deformation coefficient and Poisson ratio. A parameter defined as virtual peak deviatoric stress dependent on state parameter is introduced into hyperbolic stress strain relationship to determine tangent Young's module. In addition, an existing fitting equation for isotropic compression curves and an existing dilatancy equation, which can consider the effect of state of sands, are employed to determine bulk module and volume deformation coefficient. Thirteen model constants are involved in the proposed model, the values of which are fixed for a sand over a wide range of initial void ratios and initial confining pressures. Well known experimental data for drained and undrained triaxial compression tests of Toyoura sand are successfully modeled.