Real-time Processor-in-Loop investigation of a modified non-linear state observer using sliding modes for speed sensorless induction motor drive in electric vehicles

Tracking performance and stability play a major role in observer design for speed estimation purpose in motor drives used in vehicles. It is all the more prevalent at lower speed ranges. There was a need to have a tradeoff between these parameters ensuring the speed bandwidth remains as wide as possible. This work demonstrates an improved static and dynamic performance of a sliding mode state observer used for speed sensorless 3 phase induction motor drive employed in electric vehicles (EVs). The estimated torque is treated as a model disturbance and integrated into the state observer while the error is constrained in the sliding hyperplane. Two state observers with different disturbance handling mechanisms have been designed. Depending on, how they reject disturbances, based on their structure, their performance is studied and analyzed with respect to speed bandwidth, tracking and disturbance handling capability. The proposed observer with superior disturbance handling capabilities is able to provide a wider speed range, which is a main issue in EV. Here, a new dimension of model based design strategy is employed namely the Processor-in-Loop. The concept is validated in a real-time model based design test bench powered by RT-lab. The plant and the controller are built in a Simulink environment and made compatible with real-time blocksets and the system is executed in real-time targets OP4500/OP5600 (Opal-RT). Additionally, the Processor-in-Loop hardware verification is performed by using two adapters, which are used to loop-back analog and digital input and outputs. It is done to include a real-world signal routing between the plant and the controller thereby, ensuring a real-time interaction between the plant and the controller. Results validated portray better disturbance handling, steady state and a dynamic tracking profile, higher speed bandwidth and lesser torque pulsations compared to the conventional observer

A Reduced-Order Generalized Proportional Integral Observer-Based Resonant Super-Twisting Sliding Mode Control for Grid-Connected Power Converters

This article presents a reduced-order generalized proportional-integral observer based resonant super-twisting sliding mode controller (RST-SMC) for the three-phase ac-dc converters. On the contrary to utilizing the proportional-integral controller in regulating the dc-link voltage, which may cause large undershoot/overshoot under the disturbance, the proposed voltage control strategy for the dc-link has high disturbance rejection ability and the settling time has been greatly reduced. In addition, the proposed RST-SMC in the current control loop not only preserve the merits of the sliding mode controller but also achieve the current tracking without steady-state error in the stationary \alpha - \beta frame. The effectiveness of the proposed method has been verified by a lab-constructed experimental prototype.This work was supported by Shenzhen Overseas High Level Talent Program. The work of Josep M. Guerrerork was supported by VILLUM FONDEN under the VILLUM Investigator Grant (no. 25920): Center for Research on Microgrids (CROM); www.crom.et.aau.dk

Sliding-Mode Perturbation Observer-Based Sliding-Mode Control for VSC-HVDC Systems

This chapter develops a sliding-mode perturbation observer-based sliding-mode control (POSMC) scheme for voltage source converter-based high voltage direct current (VSC-HVDC) systems. The combinatorial effect of nonlinearities, parameter uncertainties, unmodeled dynamics, and time-varying external disturbances is aggregated into a perturbation, which is estimated online by a sliding-mode state and perturbation observer (SMSPO). POSMC does not require an accurate VSC-HVDC system model and only the reactive power and DC voltage at the rectifier side while reactive and active powers at the inverter side need to be measured. Additionally, a considerable robustness can be provided through the real-time compensation of the perturbation, in which the upper bound of perturbation is replaced by the real-time estimation of the perturbation, such that the over-conservativeness of conventional sliding-mode control (SMC) can be effectively reduced. Four case studies are carried out on the VSC-HVDC system, such as active and reactive power tracking, AC bus fault, system parameter uncertainties, and weak AC gird connection. Simulation results verify its advantages over vector control and feedback linearization sliding-mode control. Then, a dSPACE-based hardware-in-the-loop (HIL) test is undertaken to validate the implementation feasibility of the proposed approach

Flexible and robust control of heavy duty diesel engine airpath using data driven disturbance observers and GPR models

Diesel engine airpath control is crucial for modern engine development due to increasingly stringent emission regulations. This thesis aims to develop and validate a exible and robust control approach to this problem for speci cally heavy-duty engines. It focuses on estimation and control algorithms that are implementable to the current and next generation commercial electronic control units (ECU). To this end, targeting the control units in service, a data driven disturbance observer (DOB) is developed and applied for mass air ow (MAF) and manifold absolute pressure (MAP) tracking control via exhaust gas recirculation (EGR) valve and variable geometry turbine (VGT) vane. Its performance bene ts are demonstrated on the physical engine model for concept evaluation. The proposed DOB integrated with a discrete-time sliding mode controller is applied to the serial level engine control unit. Real engine performance is validated with the legal emission test cycle (WHTC - World Harmonized Transient Cycle) for heavy-duty engines and comparison with a commercially available controller is performed, and far better tracking results are obtained. Further studies are conducted in order to utilize capabilities of the next generation control units. Gaussian process regression (GPR) models are popular in automotive industry especially for emissions modeling but have not found widespread applications in airpath control yet. This thesis presents a GPR modeling of diesel engine airpath components as well as controller designs and their applications based on the developed models. Proposed GPR based feedforward and feedback controllers are validated with available physical engine models and the results have been very promisin

Advances in Spacecraft Systems and Orbit Determination

"Advances in Spacecraft Systems and Orbit Determinations", discusses the development of new technologies and the limitations of the present technology, used for interplanetary missions. Various experts have contributed to develop the bridge between present limitations and technology growth to overcome the limitations. Key features of this book inform us about the orbit determination techniques based on a smooth research based on astrophysics. The book also provides a detailed overview on Spacecraft Systems including reliability of low-cost AOCS, sliding mode controlling and a new view on attitude controller design based on sliding mode, with thrusters. It also provides a technological roadmap for HVAC optimization. The book also gives an excellent overview of resolving the difficulties for interplanetary missions with the comparison of present technologies and new advancements. Overall, this will be very much interesting book to explore the roadmap of technological growth in spacecraft systems

Nonlinear predictive control for durability enhancement and efficiency improvement in a fuel cell power system

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.Peer ReviewedPostprint (author's final draft