Energy-aware MPC co-design for DC-DC converters

In this paper, we propose an integrated controller design methodology for the implementation of an energy-aware explicit model predictive control (MPC) algorithms, illustrat- ing the method on a DC-DC converter model. The power consumption of control algorithms is becoming increasingly important for low-power embedded systems, especially where complex digital control techniques, like MPC, are used. For DC-DC converters, digital control provides better regulation, but also higher energy consumption compared to standard analog methods. To overcome the limitation in energy efficiency, instead of addressing the problem by implementing sub-optimal MPC schemes, the closed-loop performance and the control algorithm power consumption are minimized in a joint cost function, allowing us to keep the controller power efficiency closer to an analog approach while maintaining closed-loop op- timality. A case study for an implementation in reconfigurable hardware shows how a designer can optimally trade closed-loop performance with hardware implementation performance

Sensitivity-based multistep MPC for embedded systems

In model predictive control (MPC), an optimization problem is solved every sampling instant to determine an optimal control for a physical system. We aim to accelerate this procedure for fast systems applications and address the challenge of implementing the resulting MPC scheme on an embedded system with limited computing power. We present the sensitivity-based multistep MPC, a strategy which considerably reduces the computing requirements in terms of floating point operations (FLOPs), compared to a standard MPC formulation, while fulfilling closed- loop performance expectations. We illustrate by applying the method to a DC-DC converter model and show how a designer can optimally trade off closed-loop performance considerations with computing requirements in order to fit the controller into a resource-constrained embedded system

Back-to-back Converter Control of Grid-connected Wind Turbine to Mitigate Voltage Drop Caused by Faults

Power electronic converters enable wind turbines, operating at variable speed, to generate electricity more efficiently. Among variable speed operating turbine generators, permanent magnetic synchronous generator (PMSG) has got more attentions due to low cost and maintenance requirements. In addition, the converter in a wind turbine with PMSG decouples the turbine from the power grid, which favors them for grid codes. In this paper, the performance of back-to-back (B2B) converter control of a wind turbine system with PMSG is investigated on a faulty grid. The switching strategy of the grid side converter is designed to improve voltage drop caused by the fault in the grid while the maximum available active power of wind turbine system is injected to the grid and the DC link voltage in the converter is regulated. The methodology of the converter control is elaborated in details and its performance on a sample faulty grid is assessed through simulation

Real-Time Power Management of A Fuel Cell/Ultracapacitor Hybrid

This thesis presents the system architecture design, system integration methodology, and real-time control of a fuel cell/ultracapacitor hybrid power system. The main objective is for the hybrid system to respond to real-world fluctuations in power without negatively impacting fuel cell life. A Proton Exchange Membrane (PEM) Fuel Cell is an electrochemical device which converts the chemical energy of pure hydrogen into electricity through a chemical reaction with oxygen. The high conversion efficiency, zero harmful emissions, high power-to-weight ratio, scalability, and low temperature operation make PEM fuel cells very attractive for stationary and portable power applications. However, fuel cells are limited in responding to fast transients in power demand, moreover power fluctuations have negative impact on fuel cell durability. This motivates the use of a supplementary energy storage device to assist the fuel cell by buffering sharp transients in power demand. The high power density, long cycle life, and efficiency of ultracapacitors make them an ideal solution for such auxiliary energy storage in a hybrid fuel cell system. The power management strategy that determines the power split between the fuel cell and ultracapacitor is key to the power following capability, long-term performance, and life-time of the fuel cell. In this thesis, a rule-based and a model predictive control strategy are designed, implemented and evaluated for power management of a fuel cell/ultracapacitor hybrid. The high-level control objectives are to respond to rapid variations in load while minimizing damaging fluctuations in fuel cell current and maintaining ultracapacitor charge (or voltage) within allowable bounds. An experimental test stand was created to evaluate the performance of the controllers. The test stand connects the fuel cell and ultracapacitor to an electronic load through two dc/dc converters, which provide two degrees of freedom, enabling independent low-level control of the DC BUS voltage and the current split between the fuel cell and ultracapacitor. Experiments show that both rule-based and model predictive power management strategies can be tuned to meet both high and low-level control objectives for a given power demand profile. However, the capability to explicitly enforce the constraints in model predictive scheme and its predictive nature in meeting power demands enables a more systematic design and results in general in smoother performance

Model-Predictive-Control for Dual-Active-Bridge Converters Supplying Pulsed Power Loads in Naval DC Micro-grids

Pulsed-Power-Loads (PPLs) are becoming prevalent in medium-voltage naval DC micro-grids. To alleviate their effects on the system, energy storages are commonly installed. For optimal performance, their interface converters need to have fast dynamics and excellent disturbance rejection capability. Moreover, these converters often need to have voltage transformation and galvanic isolation capability since common energy storage technologies like batteries and super-caps are typically assembled with low voltage strings. In order to address these issues, a Moving-Discretized-Control-Set Model-Predictive-Control (MDCS-MPC) is proposed in this paper and applied on a Dual-Active-Bridge converter. Fixed switching frequency is maintained, enabling easy passive components design. The proposed MDCS-MPC has a reduced prediction horizon, which allows low computational burden. The operating principle of the MDCS-MPC is introduced in development of a cost function that provides stiff voltage regulation. Resonance damping and sampling noise resistance can also be achieved with the proposed cost function. An adaptive step is introduced to enable fast transition. Assessments on the performance of the proposed MDCS-MPC are conducted. Comparisons with other control methods are also provided. Experimental validations on a 300V/300V 20kHz 1kW Dual-Active-Bridge converter are carried out to verify the theoretical claims. Index Terms-Isolated DC/DC converter, Dual-Active-Bridge (DAB), Model Predictive Control (MPC)

Model Predictive Control for Dual Active Bridge in Naval DC Microgrids Supplying Pulsed Power Loads Featuring Fast Transition and Online Transformer Current Minimization

Pulsed power loads (PPLs) are commonly incorporated in medium voltage dc microgrids on naval vessels. To mitigate their detrimental effects, dedicated energy storage systems can be installed and their converters need to have excellent disturbance rejection capability. To facilitate this objective, a moving-discretized-control-set model-predictive-control (MDCS-MPC) is proposed in this letter and applied on a dual-active-bridge converter. Fixed switching frequency is maintained, enabling easy passive components design. The proposed MDCS-MPC has a small number of calculating points in each switching period, which enables the implementation in standard commercial control platforms. The operating principle of the MDCS-MPC is introduced in development of a cost function that, on one hand, provides stiff voltage regulation; on the other hand, minimizes transformer current stress online. Theoretical claims are verified on a 20 kHz 1 kW dual active bridge