FPGA implementation of online finite-set model based predictive control for power electronics

Recently there has been an increase in the use of model based predictive control (MBPC) for power-electronic converters. MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. The computational burden for this control scheme however is very high and often restrictive for a good implementation. This means that a suitable technology and design approach should be used. In this paper the implementation of finite-set MBPC (FS-MBPC) in field-programmable gate arrays (FPGAs) is discussed. The control is fully implemented in programmable digital logic by using a high-level design tool. This allows to obtain very good performances (both in control quality, speed and hardware utilization) and have a flexible, modular control configuration. The feasibility and performance of the FPGA implementation of FS-MBPC is discussed in this paper for a 4-level flying-capacitor converter (FCC). This is an interesting application as FS-MBPC allows the simultaneous control of the output current and the capacitor voltages, yet the high number of possible switch states results in a high computational load. The good performance is obtained by exploiting the FPGA’s strong points: parallelism and pipe-lining. In the application discussed in this paper the parallel processing for the three converter phases and a fully pipelined calculation of the prediction stage allow to realize an area-time efficient implementation

Design choices for the prediction and optimization stage of finite-set model based predictive control

The interest in applying model-based predictive control (MBPC) for power-electronic converters has grown tremendously in the past years. This is due to the fact that MBPC allows fast and accurate control of multiple controlled variables for hybrid systems such as a power electronic converter and its load. As MBPC is a family of possible controllers rather than one single controller, several design choices are to be made when implementing MBPC. In this paper several conceptual possibilities are considered and compared for two important parts of online Finite-Set MBPC (FS-MBPC) algorithm: the cost function in the optimizations step and the prediction model in the prediction step. These possibilities are studied for two different applications of FS-MBPC for power electronics. The cost function is studied in the application of output current and capacitor voltage control of a 3-level flying-capacitor inverter. The aspect of the prediction model is studied for the stator flux and torque control of an induction machine with a 2-level inverter. The two different applications illustrate the versatility of FS-MBPC. In the study concerning the cost function firstly the comparison is made between quadratic and absolute value terms in the cost function. Comparable results are obtained, but a lower resource usage is obtained for the absolute value cost function. Secondly a capacitor voltage tracking control is compared to a control where the capacitor voltage may deviate without cost from the reference up to a certain voltage. The relaxed cost function results in better performance. For the prediction model both a classical, parametric machine model and a back propagation artificial neural network are applied. Both are shown to be capable of a good control quality, the neural network version is much more versatile but has a higher computational burden. However, the number of neurons in the hidden layer should be sufficiently high. All studied aspects were verified with experimental results and these validate the simulation results. Even more important is the fact that these experiments prove the feasibility of implementing online finite-set MBPC in an FPGA for both applications

Analysis of some design choices in model based predictive control of flying-capacitor inverters

Purpose - Flying-capacitor multilevel converters (FCC) need a passive or active regulation of the capacitor voltages. Recently the trend is towards active control, often implemented separately from the current control. The advantages of a true multi-variable control sparked the interest to apply Model Based Predictive Control (MBPC) for FCC. In this paper an objective analysis method to evaluate the effects of several design choices is presented. The effects of the weight factor selection, model simplification, and prediction horizon expansion for MBPC of a 3-level FCC are analyzed in a systematical way. Design/methodology/approach - The analysis is mainly based on the mean square error (MSE) of current and capacitor voltage. The results are analysed for different lengths of the prediction horizon and for a wide range of weight factor values. Similarly the effect of a model simplification, neglecting the neutral point voltage, is studied when implementing MBPC for FCCs while considering the computational aspects. Validation of the simulation results is done by experiments on an FPGA-based setup. Findings - Including the effect of the neutral point voltage considerably increases the current control quality and a much wider range of good values for the weight factor exists. As this good range is not critically dependent on the current amplitude it is possible to select one weight factor value for all operating points. Furthermore, it is concluded that increasing the prediction horizon increases the computational load without improving the control quality. Research limitations/implications - The effects of increasing the prediction horizon when including other controlled variables is to be investigated, as well as the robustness to modeling errors. The MSE analysis methodology is very suitable for this further research. Practical implications - For practitioners of MBPC in power electronics the paper proves that by means of simulations and the MSE one value for weight factor can be chosen for all operating points. The paper clearly shows that a practical implementation is feasible and demonstrates that neglecting the neutral point voltage is not good practice. Originality/value - The MSE-based analysis is shown to be a systematical and unbiased methodology to evaluate the effects of design choices. The results from this analysis can be directly applied in practical setups

Design of an e-bike with UltraCaps as the only energy source and with regenerative braking

The number of charge/discharge cycles that can be achieved by today’s ultracapacitors is almost 1000 times higher than that of classical batteries. From earlier research it is also known that many e-bike users experience the limited battery lifetime as a problem. These 2 facts lead to the design and building of an e-bike without batteries and only using UltraCaps as energy source. By using a newbuilt split-PI converter topology regenerative braking was enabled, and its influence on the range of the e-bike could be investigated. The e-bike is controlled by a twist-grip and all electric quantities can be visualised on a touchscreen. The paper describes the design and shows the first test results of an e-bike with a 250W hub motor and a 500F, 16; 2V UltraCap module. In the near future, the e-bike will be used as a didactic demo model to analyze power flow during cycling.status: publishe

Overview of voltage control strategies in medium voltage networks with implementation of distributed generation

The traditional voltage control in medium voltage networks no longer suffices with the increasing penetration of DG units. This paper will give an overview of possible voltage control strategies for medium voltage networks aiming to maximize the production of renewable energy. Simulations and case studies will be conducted to examine these control strategies and to compare them to the traditional voltage control in medium voltage networks. In this overview, active power curtailment, reactive voltage control and control strategies using the OLTC will be examined