Weixiang Shen

Robust sliding mode control for Steer-by-Wire systems with AC motors in road vehicles

In this paper, the modeling of steer-by-wire (SbW) systems is further studied, and a sliding mode control scheme for the SbW systems with uncertain dynamics is developed. It is shown that an SbW system, from the steering motor to the steered front wheels, is equivalent to a second-order system. A sliding mode controller can then be designed based on the bound information of uncertain system parameters, uncertain self-aligning torque, and uncertain torque pulsation disturbances, in the sense that not only the strong robustness with respect to large and nonlinear system uncertainties can be obtained but also the front-wheel steering angle can converge to the handwheel reference angle asymptotically. Both the simulation and experimental results are presented in support of the excellent performance and effectiveness of the proposed scheme.

Adaptive gain sliding mode observer for state of charge estimation based on combined battery equivalent circuit model

An adaptive gain sliding mode observer (AGSMO) for battery state of charge (SOC) estimation based on a combined battery equivalent circuit model (CBECM) is presented. The errors convergences of the AGSMO for the SOC estimation are proved by Lyapunov stability theory. The AGSMO has a capability of compensating modeling errors caused by the parameters variation of the CBECM and minimizing chattering level in SOC estimation. The lithium-polymer battery (LiPB) is used to conduct experiments for extracting the parameters of the CBECM and verifying the effectiveness of the proposed AGSMO for the SOC estimation.

Charging algorithms of lithium-ion batteries: An overview

This paper presents the overview of charging algorithms for lithium-ion batteries, which include constant current-constant voltage (CC/CV), variants of the CC/CV, multistage constant current, pulse current and pulse voltage. The CC/CV charging algorithm is well developed and widely adopted in charging lithium-ion batteries. It is used as a benchmark to compare with other charging algorithms in terms of the charging time, the charging efficiency, the influences on battery life and other aspects, which can serve as a convenient reference for future work in developing a charger for lithium-ion battery.

Robust control for steer-by-wire systems with partially known dynamics

In this paper, a robust control scheme (RCS) for Steer-by-Wire (SbW) systems with partially known dynamics is proposed. It is shown that an SbW system can be represented by a nominal model and an unknown portion. A nominal feedback controller can then be used to stabilize the nominal model and a sliding mode compensator (SMC) is designed to remove the effects of both the unknown system dynamics and uncertain road conditions on the steering performance. For practical consideration, robust exact differentiator (RED) technique is utilized to estimate the derivatives of the position signals for controller design. It is further shown that the designed RCS is able to guarantee a robust steering performance against system and road uncertainties. The comparative experimental studies are given to verify the excellent performance of the proposed RCS for SbW systems.

Robust Adaptive Sliding-Mode Observer Using RBF Neural Network for Lithium-Ion Battery State of Charge Estimation in Electric Vehicles

This paper presents a robust sliding-mode observer (RSMO) for state-of-charge (SOC) estimation of a lithium-polymer battery (LiPB) in electric vehicles (EVs). A radial basis function (RBF) neural network (NN) is employed to adaptively learn an upper bound of system uncertainty. The switching gain of the RSMO is adjusted based on the learned upper bound to achieve asymptotic error convergence of the SOC estimation. A battery equivalent circuit model (BECM) is constructed for battery modeling, and its BECM is identified in real time by using a forgetting-factor recursive least squares (FFRLS) algorithm. The experiments under the discharge current profiles based on EV driving cycles are conducted on the LiPB to validate the effectiveness and accuracy of the proposed framework for the SOC estimation.

Adaptive gain sliding mode observer for state of charge estimation based on combined battery equivalent circuit model in electric vehicles

An adaptive gain sliding mode observer (AGSMO) for battery state of charge (SOC) estimation based on a combined battery equivalent circuit model (CBECM) is presented. The errors convergences of the AGSMO for the SOC estimation are proved by Lyapunov stability theory. The AGSMO has a capability of compensating modeling errors caused by the parameters variation of the CBECM and minimizing chattering level in SOC estimation. The lithium-polymer battery (LiPB) is used to conduct experiments for extracting the parameters of the CBECM and verifying the effectiveness of the proposed AGSMO for the SOC estimation.

A comparative study of observer design techniques for state of charge estimation in electric vehicles

A well-known Luenburger observer and two sliding mode observers (SMO) for battery state of charge (SOC) estimation based on an improved battery equivalent circuit are presented. The comparison of their SOC estimation results is discussed. The testing data under different discharge current profiles generated by DUALFOIL battery simulation program are used to extract the circuit model parameters and verify the effectiveness of the observers for the SOC estimation. It shows that two sliding mode based SOC observers have robust tracking performance and provide more accurate SOC estimation in electric vehicle driving conditions.

Sliding Mode Observer for State of Charge Estimation Based on Battery Equivalent Circuit in Electric Vehicles

Abstract The sliding mode observer (SMO) for battery state of charge (SOC) estimation based on the improved battery equivalent circuit is presented. The convergence of the SMO is proved by Lyapunov stability theory. The advantage of the SMO is that the modelling errors caused by the variation parameters of circuit model can be compensated. Three sets of the testing data under different discharge current profiles generated by DUALFOIL battery simulation program are used to extract the circuit model parameters and to verify the effectiveness of the proposed SMO for the SOC estimation. It shows that the proposed SOC observer can provide robust tracking performance and accurate SOC estimation in electric vehicle driving conditions.

A review on transient stability of DFIG integrated power system

With the increasing penetration of doubly fed induction generators (DFIGs), the impact of the DFIG on transient stability attracts great attention. Transient stability is largely dominated by generator types in the power system, and the dynamic characteristics of DFIG wind turbines are different from that of the synchronous generators in the conventional power plants. The analysis of the transient stability on DFIG integrated power systems has become a very important issue. This paper reviews the current research on the issue from two aspects. One is to describe the methods to improve the fault ride through capability of DFIG wind turbines and the other is to analyse the impact of the DFIG wind farm on transient stability of power systems.

Experimental comparison of charging algorithms for a lithium-ion battery

Comparing with conventional charging algorithm of constant current and constant voltage (CC/CV) for lithium ion batteries, many charging algorithms are proposed to improve charging time, charging efficiency and cycle life. However, the comparisons were conducted only between the charging algorithms and the CC/CV for different lithium ion batteries. In this paper, a new testing platform based on LabVIEW is developed to investigate various charging algorithms under the same battery with similar testing conditions, where the platform includes programmable power supply and electronic load. The experimental results of battery voltage, current and temperature are sampled to calculate the ampere hour and energy efficiencies and the times for charging up to 50%, 80% and 100% of normal capacity. The maximum temperature difference for all the charging algorithms during an entire charging period is less than 3 degree which indicates that all charging algorithms have similar effect on battery cycle life to the CC/CV.