Energy Optimal Control Research Articles

Energy Efficient Speed and Position Control of Electric Drives with Pmsm

A new speed and position controller respecting principles of near-energy optimal control for the drives with permanent magnet synchronous motor are developed as a contribution to the energy saving and environmental protection. Two various approaches to the energy saving controller design are analysed. The first approach is strictly based on energy optimal control theory and derives analytical solutions of the control problem. The second approach develops approximated solution for the drive position controller when the optimal speed trajectory is modified to correspond to the triangular and trapezoidal profile. This approach enables not only to compare energy demands of the individual control system design but also to exploit near-energy optimal controller for any controlled industrial drive

Two-layer self-powered active seismic isolation floor

In this paper, a self-powered active seismic isolation floor is proposed to solve safety concern about active control in case of an electricity shortage. The self-powered active seismic isolation floor is composed of two layers named Unit B and Unit T. This self-powered system is based on the idea of electric power regeneration. Two kinds of actuators act in it. The two actuators are controlled by different control methods; the two control methods are constructed as a distributed control. One actuator at Unit B acts as a generator during deceleration based on an energy optimal control that is superior in energy regeneration, and the other one at Unit T acts to control vibration using charging energy at Unit B based on conventional control method that is effective in vibration reduction. The control design method and its parameters are shown considering performance and energy. In addition, the displacement of the top layer which defines a required clearance of the two-layer seismic isolation floor can be reduced by allowing for large drift of the small layer between Unit B and Unit T. It is showed that the proposed system uses only charged battery at an initial state, and its control performance is superior to that of a two-layer passive seismic isolation floor by time-history analysis.

Hybrid Control of a Wind Induction Generator Based on Grey–Elman Neural Network

This brief presents the design of an optimal wind energy control system for maximum power point tracking. With the help of a grey predictor for the preprocessor, a high-performance online training Elman neural network (ENN) is designed to derive the turbine speed needed to extract maximum power from wind. Moreover, the connective weights of the improved ENN are trained online by the backpropagation learning algorithm. Compared to earlier methods, better results are obtained when the ENN controller is used together with the grey system modeling approach. Performance of the proposed approach is verified by the experimental results.

Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov Decision Process

Abstract Electricity demand response has been considered as a critical methodology to realize the strategy of sustainable development for manufacturing enterprises by effectively reducing the increasing electricity demand and Greenhouse Gas emissions. Most existing studies about the electricity demand response implementation focus on either the supply side management, e.g ., policy making, price setting, or the customer side applications for the end-users in residential and commercial building sectors. As for the industrial sector, only a few papers utilizing the long term scheduling methodology to reduce the electricity consumption during peak periods are available. Little work has been implemented on the decision-making for the real time electricity demand response in industrial manufacturing systems considering system throughput constraint. In this paper, an analytical model is established to identify the optimal energy control actions and estimate the potential capacity of power demand reduction of typical manufacturing systems during the period of demand response event without compromising system production. Markov Decision Process is used to model the complex interaction between the adopted demand control actions and the system state evolutions. A numerical case study on a section of an automotive assembly line is used to illustrate the effectiveness of the proposed approach.

Effect of minimum energy control on steel loss in VR stepper motor

Abstract This research presents a 3D FE method for the simulation of the variable reluctance stepper motor dynamics. The proposed model is used to obtain the optimal minimum energy control law that minimizes the energy injected by the controller. The method is based on the strong coupling of field - circuit equations and extended to eddy current, motion and nonlinearity problem. The linearization technique for the coupled problem is presented. Also the lamination of the motor core is considered. In the paper the open - loop control problem is analyzed. The proposed model is validated by the comparison with measurements. Next, to demonstrate the effectiveness of the proposed optimal minimum energy control method is applied. In both cases, the examination of the variable reluctance stepper motor dynamics and the steel loss in the core is presented and compared

Optimal Energy Control Strategy Design for a Hybrid Electric Vehicle

A heavy-duty parallel hybrid electric truck is modeled, and its optimal energy control is studied in this paper. The fundamental architecture of the parallel hybrid electric truck is modeled feed-forwardly, together with necessary dynamic features of subsystem or components. Dynamic programming (DP) technique is adopted to find the optimal control strategy including the gear-shifting sequence and the power split between the engine and the motor subject to a battery SOC-sustaining constraint. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement on the fuel economy can be achieved in the heavy-duty vehicle cycle from the natural driving statistics.

D15 エネルギー最適制御に基づく建物・設備連成系の振動制御(M-OS2-2 免震・制振の制御系設計,M-OS2 建築・建設構造物の耐震・免震・制振,「海を越え,国を越え,世代を超えて!」)

D15 エネルギー最適制御に基づく建物・設備連成系の振動制御(M-OS2-2 免震・制振の制御系設計,M-OS2 建築・建設構造物の耐震・免震・制振,「海を越え,国を越え,世代を超えて!」)

Optimal control of nonlinear objects of engineering thermophysics

The piecewise continuous (relay) nature of lumped control actions in problems of timeand energy-optimal control of a wide range of distributed-parameter nonlinear objects of engineering thermophysics is established. On this basis, the required programmed controls in a number of practical situations can be found by the proposed algorithmically precise (alternance) method. As an example, which is of independent interest, the problem of optimal control of nonlinear models of induction heating of metal semi-products before subsequent pressure treatment is considered.

AN OPTIMAL ENERGY CONTROL OF A FLEXIBLE PLATE WITH VISCOELASTIC CONDITIONS

An optimal control problem of a flexible thin plate formulated bypartial differential equations with viscoelastic boundary conditionsis studied in this paper. The problem is written in standard form oflinear infinite dimensional system in an appropriate energy Hilbertspace. The semigroup approach of linear operators is adopted ininvestigating well-posedness of the closed loop system. An optimalenergy control is proposed, and existence and uniqueness of theoptimal control are demonstrated, and an approximation theorem isproved in terms of semigroup approach and geometric method.

Full paper: Environmental modeling for the optimal energy control of subway stations

Full paper: Environmental modeling for the optimal energy control of subway stations

Environmental modeling for the optimal energy control of subway stations

Purpose Underground transportation systems are big energy consumers and have a significant impact on energy consumption at regional level. One third of the networks’ energy is required for operating the subsystems of metro stations and surroundings, such as ventilation, vertical transportation and lightning. Although a relatively small percentage of energy can be saved with optimal management of these subsystems, in absolute terms this means large energy savings are obtained. Furthermore, optimal management is a big opportunity for energy efficiency since it involves much smaller investments than those usually applied to transportation by providing new ways for sustainable energy saving solutions. In this perspective, the EU-funded R&D project SEAM4US (Sustainable Energy Management for Underground Stations) is aimed at defining a technological and methodological framework for optimized energy management in public underground spaces, which will be applied to the dynamic control of the energy consumption in Barcelona Passeig de Gracia subway station. Method The development of a new class of predictive control logics, behaving consistently in changing environments is at the core of the optimal energy management approach and it is one of the main objectives of this research. This class of control systems is based on advanced environmental models, directly coupled with an environment monitoring sensor network, that is capable of interpreting the sensed data (both indoor and environmental) and of forecasting future states. In order to achieve the necessary level of robustness these models must be able to learn from previous states so they can adapt to the varying environment. The development of this class of environmental models for large underground environments like subway stations involves the elaboration and the integration of different simulation models concerning natural and forced ventilation, passenger movement, lighting systems, and their integration in a unique formals statistical framework, which is able to manage the uncertainty affecting the sensed data and to learn from the data flow. Results & Discussion We will outline the methodological approach to the development of the Passeig de Gracia environmental models for the optimal control of its energy consumption. The adopted hybrid modeling solutions, integrating different classes of simulation means in a unique Bayesian framework4, and a preliminary architecture of the overall control system will be presented.

Nonlinear Phenomena in Biology and Medicine

Nonlinear Phenomena in Biology and Medicine

Energy Conservation and Interference Mitigation: From Decoupling Property to Win-Win Strategy

This paper studies the problem of energy conservation of mobile terminals in a multi-cell TDMA network supporting real-time sessions. The corresponding optimization problem involves joint scheduling, rate control, and power control, which is often highly complex to solve. To reduce the solution complexity, we decompose the overall problem into two sub-problems: intra-cell energy optimization and inter-cell interference control. The solution of the two subproblems results in a win-win situation: both the energy consumptions and inter-cell interference are reduced simultaneously. We simulate our decomposition method with the typical parameters in WiMAX system, and the simulation results show that our decomposition method can achieve an energy reduction of more than 70% compared with the simplistic maximum transmit power policy. Furthermore, the inter-cell interference power can be reduced by more than 35% compared with the maximum transmit power policy. We find that the interference power stays largely constant throughout a TDMA frame in our decomposition method. Based on this premise, we derive an interesting decoupling property: if the idle power consumption of terminals is no less than their circuit power consumption, or when both are negligible, then the energy-optimal transmission rates of the users are independent of the inter-cell interference power.

Research on the Time Factor of Li-Ion Battery for Vehicle-to-Grid (V2G) Implementation and Charging Station Application

An outline of electric vehicles industry in the national smart grid plan and a conceptual framework for the vehicle-to-grid implementation in China is presented, and the relationship between battery energy package and smart grid is also discussed in this paper. The analysis and research based on the energy package management and charging station requirements are stated. This paper also does research on reasonable charge and discharge of the Li-ion battery with the performance degradation, which are the key issues of the development of electric vehicles. At last the paper will discuss briefly on the fast charge method, which saves time of charge battery and favors life span of battery system. When plenty of electric vehicles connecting to the grid, advanced energy scheduling and optimization control strategy of Li-ion battery demand consideration of time factor and the gird needs.

On the achievable performance using variable geometry active secondary suspension systems in commercial vehicles

There is a need to further improve driver comfort in commercial vehicles. The variable geometry active suspension offers an interesting option to achieve this in an energy efficient way. However, the optimal control strategy and the overal performance potential remains unclear. The aim of this paper is to quantify the level of performance improvement that can theoretically be obtained by replacing a conventional air sprung cabin suspension design with a variable geometry active suspension. Furthermore, the difference between the use of a linear quadratic (LQ) optimal controller and a classic skyhook controller is investigated. Hereto, an elementary variable geometry actuator model and experimentally validated four degrees of freedom quarter truck model are adopted. The results show that the classic skyhook controller gives a relatively poor performance while a comfort increase of 17–28% can be obtained with the LQ optimal controller, depending on the chosen energy weighting. Furthermore, an additional 75% comfort increase and 77% energy cost reduction can be obtained, with respect to the fixed gain energy optimal controller, using condition-dependent control gains. So, it is concluded that the performance potential using condition-dependent controllers is huge, and that the use of the classic skyhook control strategy should, in general, be avoided when designing active secondary suspensions for commercial vehicles.

Energy-Optimal Control of Plug-in Hybrid Electric Vehicles for Real-World Driving Cycles

Plug-in hybrid electric vehicles (PHEVs) are currently recognized as a promising solution for reducing fuel consumption and emissions due to the ability of storing energy through direct connection to the electric grid. Such benefits can be achieved only with a supervisory energy management strategy that optimizes the energy utilization of the vehicle. This control problem is particularly challenging for PHEVs due to the possibility of depleting the battery during usage and the vehicle-to-grid interaction during recharge. This paper proposes a model-based control approach for PHEV energy management that is based on minimizing the overall CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions produced-directly and indirectly-from vehicle utilization. A supervisory energy manager is formulated as a global optimal control problem and then cast into a local problem by applying the Pontryagin's minimum principle. The proposed controller is implemented in an energy-based simulator of a prototype PHEV and validated on experimental data. A simulation study is conducted to calibrate the control parameters and to investigate the influence of vehicle usage conditions, environmental factors, and geographic scenarios on the PHEV performance using a large database of regulatory and “real-world” driving profiles.

Optimal control of a subway train with regard to the criteria of minimum energy consumption

A mathematical formulation of the problem of determining energy optimal train control with regenerative breaking and its solution based on the maximum principle are presented. The results of analysis of the train model and train model errors influence on the optimal trajectory are presented. Examples of energy optimal trajectories on the lines of the Moscow and Hanoi Metro are shown.

Energy optimal spacecraft attitude control subject to convergence rate constraints

Attitude control of operational satellites is still predominantly performed by standard controllers such as Proportional plus Derivative (PD) control laws, which are still preferred for implementation to the computationally intensive nonlinear optimal control techniques, representing higher implementation complexity. In this paper, an inverse optimal control approach based on phase space geometry is presented, which is easy to implement and free from numerical and computational issues. The optimal control objective is to minimize a norm of the control torque subject to a rapidity constraint on the convergence rate of a Lyapunov function, under the effect of a benchmark controller. The proposed optimization method is shown to significantly enhance the torque-rapidity trade-off compared to the benchmark controller, chosen to be a PD law then a sliding mode controller. The inverse optimal control scheme is implemented on an air bearing table experimental platform.

An Air Conditioning Energy Optimization Control System for a Telecom Building

According to the problems of the existing air conditioning system of the telecom building, a new air conditioning energy optimization control system was designed and constructed. In this system, a refined control that covers from the cold source to the air conditioning terminal units can be achieved. The system worked efficiently by applying various control technologies. It is reliable and easy to operate. Significant energy savings has been achieved since its application in 2010.

Energy performance and optimal control of air-conditioned buildings with envelopes enhanced by phase change materials

Studies are conducted to investigate the impacts of shape-stabilized phase change material (SSPCM) and different control strategies on the energy consumption and peak load demand as well as electricity cost of building air-conditioning systems at typical summer conditions in two climates (subtropical and dry continental climates). An office building using a typical variable air volume (VAV) air-conditioning system was selected and simulated as the reference building in this study. Its envelopes were enhanced by integrating the SSPCM layers into its walls while the air-conditioning system and other configurations of the building remained unchanged. The building system was tested under two typical weather conditions and two typical electricity pricing policies (i.e. time-based pricing and energy-plus-demand-based pricing). Test results show that the use of SSPCM in the building could reduce the building electricity cost significantly (over 11% in electricity cost reduction and over 20% in peak load reduction), under two pricing policies by using load shifting control and demand limiting control respectively. This paper presents the test results and the evaluation on the energy performance and the optimal control strategies of air-conditioned commercial buildings with envelopes enhanced by SSPCM.