Kyunghwan Choi

This study proposes an advanced current and position sensor fault diagnosis mechanism for permanent magnet synchronous motor (PMSM) applications. Machine nonlinear dynamics as well as parameter and load uncertainties are addressed. The features of the results of this study are summarized as follows: 1) a proportional-type full-state observer is combined with a disturbance observer to deal with the model uncertainties, 2) a partial optimal process is introduced for determining the observer gain,

The equivalent consumption minimization strategy (ECMS) has been considered as a practical energy management strategy for the hybrid electric vehicles (HEVs) because it can be implemented in real time while providing satisfactory performance. However, it is still challenging to adjust an equivalent factor (EF) to its own optimal value in real time because the EF is fundamentally affected by the current driving condition. Although many adaptive ECMSs (A-ECMSs) have been developed to adjust the EF

In this paper, a new method is proposed for the real-time estimation of the full parameters of a permanent magnet synchronous motor (PMSM) that is based on the stator current ripple model. By introducing the stator current ripple model together with the known two state equations for the d- and q-axes currents, we resolve the rank deficiency problem, thus enabling real-time full parameter estimation even in the steady state. A signal processing technique for removing adverse effects from noises a

This study presents a real-time optimal torque control scheme for interior permanent magnet synchronous motors (IPMSMs). The proposed scheme enables computation of optimal current reference for a torque reference under all operating regions, including the maximum torque per ampere (MTPA), flux weakening (FW), maximum current (MC), and maximum torque per voltage (MTPV), using numerical optimization techniques to simplify the problems and obtain the corresponding solutions with reduced computation

Electrotactile stimulation has been used to provide sensory information of forearm prosthesis to users. Although conventional sensory feedback method, where one electrode expresses sensory information of only one finger, could provide force information of three fingers by using three electrodes, it showed less cognitive accuracy when more than two electrodes were stimulated simultaneously compared to individual stimulation. To improve the cognitive accuracy, we presented a sensory feedback metho

One of the long-standing challenges in upper limb prosthetics is restoring the sensory feedback that is missing due to amputation. Two approaches have previously been presented to provide various types of sensory information to users, namely, multi-modality sensory feedback and using an array of single-modality stimulators. However, the feedback systems used in these approaches were too bulky to be embedded in prosthesis sockets. In this paper, we propose an electrocutaneous sensory feedback met

This study presents a computationally efficient model predictive torque control (MPTC) method for permanent magnet synchronous machines (PMSMs). The existing MPTC methods require solving complex optimization problems in iterations; this approach is computationally demanding. In contrast, the proposed MPTC transforms the optimization problem into two subproblems and derives the corresponding solutions explicitly using numerical techniques, which entail linearization of the torque function and cur

The predictive energy management (PEM) problem for hybrid electric powertrains is challenging to solve in real time, mainly due to the nonconvexity from the battery state of energy (SOE) model, which is nonlinear. This letter proposes a control-oriented battery model consisting of a stochastic linear SOE model and a quadratic power loss model to realize real-time PEM. The stochastic linear model describes the SOE trajectory from an average point of view. The quadratic power loss model describes

This Letter proposes a novel technique for automatic position offset calibration for permanent‐magnet synchronous machine (PMSM) drives. Contrary to existing methods, the proposed technique estimates and compensates for the position offset without using machine true parameters or signal injection, which is possible under the condition of zero‐current control at high enough speed where parameter‐dependent terms are eliminated. To achieve this condition using uncertain parameters, speed control wi

This paper presents an offset-free global tracking control algorithm for the input-constrained plants modeled as controllable and open-loop strictly stable linear time invariant (LTI) systems. The contribution of this study is two-fold: First, a global tracking control law is devised in such a way that it not only leads to offset-free reference tracking but also handles the input constraints using the invariance property of a projection operator embedded in the proposed disturbance observer (DOB

The predictive energy management (PEM) of hybrid electric vehicles (HEVs) is a challenging problem of trajectory optimization involving future information. Most previous studies have presented intuitive methods for selecting parameters that represent future information. However, such intuitive methods lack theoretical analysis and do not guarantee global optimality. This study adopts the novel perspective that the PEM problem can be analytically solved so as to ensure near-optimal efficiency. Th

This study suggests a non‐linear output voltage tracking controller for DC/DC boost converters in the form of a classical cascade control structure. Non‐linearities in the converter dynamics as well as parameter uncertainties and load variations are considered. The first contribution of this study is the design of an auto‐tuner, which automatically adjusts the control gain according to the output voltage error to enhance transient performance. The second contribution involves proving that the cl