Control Over Dispute-System Design and Mandatory Commercial Arbitration

This article argues that mandatory arbitration is not itself the problem. The problem is instead that in some instances, one party to the dispute has exclusive control of the design of the dispute-resolution system. Consequently, research on mandatory arbitration should concentrate on who is structuring it, how they structure it, why this is so and how these choices affect dispute outcomes

Nonlinear state-observer techniques for sensorless control of automotive PMSM's, including load-torque estimation and saliency

The paper investigates various non-linear observer-based rotor position estimation schemes for sensorless control of permanent magnet synchronous motors (PMSMs). Attributes of particular importance to the application of brushless motors in the automotive sector, are considered e.g. implementation cost, accuracy of predictions during load transients, the impact of motor saliency and algorithm complexity. Emphasis is given to techniques based on model linearisation during each sampling period (EKF); feedback-linearisation followed by Luenberger observer design based on the resulting �linear� motor characteristics; and direct design of non-linear observers. Although the benefits of sensorless commutation of PMSMs have been well expounded in the literature, an integrated approach to their design for application to salient machines subject to load torque transients remains outstanding. Furthermore, this paper shows that the inherent characteristics of some non-linear observer structures are particularly attractive since they provide a phase-locked-loop (PLL)-type of configuration that can encourage stable rotor position estimation, thereby enhancing the overall sensorless scheme. Moreover, experimental results show how operation through, and from, zero speed, is readily obtainable. Experimental results are also employed to demonstrate the attributes of each methodology, and provide dynamic and computational performance comparisons

GA-based tuning of nonlinear observers for sensorless control of IPMSMs

The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous machines (IPMSMs). Emphasis is given to techniques based on feedback linearisation followed by Luenberger observer design, and direct design of nonlinear observers. Genetic algorithms (GAs) based on the principles of evolution, natural selection and genetic mutation are employed to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist, with results included to demonstrate the enhanced performance attributes offered by observers tuned in this way

GA-tuning of nonlinear observers for sensorless control of automotive power steering IPMSMs

The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous motors (IPMSMs) for use in future automotive power steering systems. Specifically, emphasis is given to techniques based on feedback-linearisation followed by classical Luenberger observer design, and direct design of non-linear observers. Genetic algorithms (GAs), using the principles of evolution, natural selection and genetic mutation, are introduced to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist. Experimental measurements from an automotive power steering test-facility are included, to demonstrate the enhanced performance attributes offered by tuning the proposed observer schemes, online, in this manner

Aligning Employees Through \u3ci\u3eLine of Sight\u3c/i\u3e

Aligning employees with the firm’s larger strategic goals is critical if organizations hope to manage their human capital effectively and ultimately attain strategic success. An important component of attaining and sustaining this alignment is whether employees have “line of sight” to the organization’s strategic objectives. We illustrate how the translation of strategic goals into tangible results requires that employees not only understand the organization’s strategy, they must accurately understand what actions are aligned with realizing that strategy. Using recent empirical evidence, theoretical insights, and tangible examples of exemplary firm practices, we provide thought-leaders with a comprehensive view of LOS, how it is created, how it can be enhanced or stifled, and how it can be effectively managed. We integrate LOS with current thinking on employee alignment to help managers more effectively benefit from understanding human capital potential

Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles

Abstract—This paper describes the application of state-estimation techniques for the real-time prediction of the state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, approaches based on the well-known Kalman Filter (KF) and Extended Kalman Filter (EKF), are presented, using a generic cell model, to provide correction for offset, drift, and long-term state divergence—an unfortunate feature of more traditional coulomb-counting techniques. The underlying dynamic behavior of each cell is modeled using two capacitors (bulk and surface) and three resistors (terminal, surface, and end), from which the SoC is determined from the voltage present on the bulk capacitor. Although the structure of the model has been previously reported for describing the characteristics of lithium-ion cells, here it is shown to also provide an alternative to commonly employed models of lead-acid cells when used in conjunction with a KF to estimate SoC and an EKF to predict state-of-health (SoH). Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior to more traditional techniques, with accuracy in determining the SoC within 2% being demonstrated. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack

State-of-charge and state-of-health prediction of lead-acid batteries for hybrid electric vehicles using non-linear observers

The paper describes the application of state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Approaches based on the extended Kalman filter (EKF) are presented to provide correction for offset, drift and state divergence - an unfortunate feature of more traditional coulomb-counting techniques. Experimental results are employed to demonstrate the relative attributes of the proposed methodolog

Sensorless control of deep-sea ROVs PMSMs excited by matrix converters

The paper reports the development of model-based sensorless control methodologies for driving PMSMs using matrix converters. In particular, experimental results show that observer-based state-estimation techniques normally employed for sensorless control of PMSMs using voltage source inverters (VSIs), can be readily exported to matrix converter counterparts with minimal additional computational overhead. Furthermore, zero speed start-up and speed reversal are experimentally demonstrated. Finally, the observer is designed to be fault tolerant such that upon detection of a broken terminal (phase fault), the PMSM remains operational and could be utilized to provide a limp-home capabilit

Observer techniques for estimating the state-of-charge and state-of-health of VRLABs for hybrid electric vehicles

The paper describes the application of observer-based state-estimation techniques for the real-time prediction of state-of-charge (SoC) and state-of-health (SoH) of lead-acid cells. Specifically, an approach based on the well-known Kalman filter, is employed, to estimate SoC, and the subsequent use of the EKF to accommodate model non-linearities to predict battery SoH. The underlying dynamic behaviour of each cell is based on a generic Randles' equivalent circuit comprising of two-capacitors (bulk and surface) and three resistors, (terminal, transfer and self-discharging). The presented techniques are shown to correct for offset, drift and long-term state divergence-an unfortunate feature of employing stand-alone models and more traditional coulomb-counting techniques. Measurements using real-time road data are used to compare the performance of conventional integration-based methods for estimating SoC, with those predicted from the presented state estimation schemes. Results show that the proposed methodologies are superior with SoC being estimated to be within 1% of measured. Moreover, by accounting for the nonlinearities present within the dynamic cell model, the application of an EKF is shown to provide verifiable indications of SoH of the cell pack