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.

An innovative inertial parameters identification method for non-cooperative space targets based on electrostatic interaction

Inertial characteristics of non-cooperative targets are crucial for space capture and sub-sequent on-orbit servicing.Previous methods for identifying inertial parameters involve proximity operations,which are associated with the risk of collision with non-cooperative targets.This paper introduces a long-range,contactless method for identifying the inertial parameters of a non-cooperative target during the pre-capture phase.Specifically,electrostatic interaction is used as an external excitation to alter the target's motion.A force estimation algorithm that uses measure-ments from visual and potential sensors is proposed to estimate the electrostatic interaction and eliminate the need for force sensors.Furthermore,a recursive estimation-identification framework is presented to concurrently estimate the coupled motion state,weak electrostatic interaction,and inertial parameters of the target.The simulation results show that the proposed method extends the identification distance to 170 times that of the previous method while maintaining high identifica-tion precision forall parameters.

An inertial parameter identification method of eliminating system damping effect for a six-degree-of-freedom parallel manipulator

A new simple and effective inertial parameter identification method based on sinusoidal vibrations of a six-degree-of-freedom parallel manipulator is proposed. Compared with previously known identification algorithms, the advantages of the new approach are there is no need to design the excitation trajectory to consider the condition number of the observation matrix and the inertial matrix can be accurately defined regardless of the effect of viscous friction. In addition, the use of a sinusoidal exciting trajectory allows calculation of the velocities and accelerations from the measured position response. Simulations show that the new approach has acceptable tolerance of dry friction when using a simple coupling parameter modified formula. The experimental application to the hydraulically driven Stewart platform demonstrates the capability and efficiency of the proposed identification method.

Global modeling and simulation of vehicle to analyze the inertial parameters effects

This paper mainly studies the comparison of the global vehicle models and the effects of the inertial parameters due to the center of gravity(CG)positions when we consider that the vehicle has only one CG.This paper proposes a new nonlinear model vehicle model which considers both unsprung mass and sprung mass CG.The CG positions and inertial parameters effects are analyzed in terms of the published vehicle dynamics models.To this end,two 14 degree-of-freedom(DOF)vehicle models are developed and compared to investigate the vehicle dynamics responses due to the different CG height and inertial parameters concepts.The proposed models describe simultaneously the vehicle motion in longitudinal,lateral and vertical directions as well as roll,pitch and yaw of the vehicle about corresponding axis.The passive and active moments and the forces acting on the vehicle are also described and they are considered as a direct consequence of acceleration,braking and steering maneuvers.The proposed model M1 takes both the CG of sprung mass,unsprung mass and total vehicle mass into account.The second model M2 assumes that the vehicle is one solid body which has a single CG as reported in majority of literature.The two vehicle models are compared and analyzed to evaluate vehicle ride and handling dynamic responses under braking/acceleration and cornering maneuvers.Simulation results show that the proposed model M1 could offer analytically some abilities and driving performances,as well as improved roll and pitch in a very flexible manner compared to the second model M2.

Robust Adaptive Attitude Control for Non-rigid Spacecraft With Quantized Control Input

In this paper,an adaptive backstepping control scheme is proposed for attitude tracking of non-rigid spacecraft in the presence of input quantization,inertial uncertainty and external disturbance.TThe control signal for each actuator is quantized by sector-bounded quantizers,including the logarithmic quantizer and the hysteresis quantizer.By describing the impact of quantization in a new affine model and introducing a smooth function and a novel form of the control signal,the influence caused by input quantization and external disturbance is properly compensated for.Moreover,with the aid of the adaptive control technique,our approach can achieve attitude tracking without the explicit knowledge of inertial parameters.Unlike existing attitude control schemes for spacecraft,in this paper,the quantization parameters can be unknown,and the bounds of inertial parameters and disturbance are also not needed.In addition to proving the stability of the closed-loop system,the relationship between the control performance and design parameters is analyzed.Simulation results are presented to illustrate the effectiveness of the proposed scheme.

Practical Model for Real Structure and Performance of Heavy Vehicles

In this paper, a new practical model for real heavy vehicle structure is developed to investigate dynamic responses under steering/acceleration or braking maneuvers. The generalized six DoFs （degrees-of-freedom） nonlinear vehicle model M1 including longitudinal, lateral, yaw, vertical, roll and pitch dynamics is validated using the measured data reported in different studies. This model takes the CG （center of gravity） of sprung mass, unsprung mass and total vehicle mass into account. Based on this model, the effects of the inertia parameters on the vehicle dynamic responses are investigated for more comprehensive assessments of the model structure. Another nonlinear vehicle model 342 derived from M1 which assumes that the vehicle has a single CG as reported in literature is also developed. The dynamic responses of the vehicle model Mj are compared with those of the model M2 to demonstrate the performance potential of the proposed nonlinear model. The results of dynamic responses with the nonlinear vehicle model MI suggest that the model could offer considerable potential in realizing enhanced ride and handling performance, as well as improved roll and pitch properties in a flexible manner.

Compound Pendulum Modeling and Resonant Frequency Analysis of the Lower Limbs for the Wearer and Exoskeleton

An innovative lower extremity exoskeleton with hybrid leg structures is proposed in this paper. The compound pendulum model is applied to analyze the swing motion during walking for the wearer and the exoskeleton respectively. The expression of the resonant period for the human lower limb is obtained and the optimum stride frequency, at which the energy expenditure for walking is the least, coincides with the stride frequency of strolling well. As for the exoskeleton, the relationship between the inertial parameters and the resonant period of the hybrid leg is established. To minimize the walking energy cost for the exoskeleton, the inertial parameter design must guarantee that the resonant period of the hybrid leg coincides with the actual stride period of the wearer. The resonant period of the hybrid leg is also influenced by the scissor angle which determines the distance between the hip and the ankle of the lower extremity exoskeleton （SJTU-EX） and can be adjusted to match different stride frequencies of various motions by the proper scissor angle planning.