Predictive Model of Adaptive Cruise Control Speed to Enhance Engine Operating Conditions
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This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by optimizing the engine operating conditions (EOC) considering vehicle level vectors (VLV) (body parameter, environment, driver behaviour) as the affecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the VLV. We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived at each second. Thus, three eligible speed values are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps. A performance comparison between predicted and constant ACCSSP’s indicates that the predictive model outperforms constant ACCSSP.Keywords:
Operating point
Model Predictive Control
Operating speed
Constant (computer programming)
Feature (linguistics)
This article presents a novel methodology to predict the optimal adaptive cruise control set speed profile (ACCSSP) by optimizing the engine operating conditions (EOC) considering vehicle level vectors (VLV) (body parameter, environment, driver behaviour) as the affecting parameters. This paper investigates engine operating conditions (EOC) criteria to develop a predictive model of ACCSSP in real-time. We developed a deep learning (DL) model using the NARX method to predict engine operating point (EOP) mapping the VLV. We used real-world field data obtained from Cadillac test vehicles driven by activating the ACC feature for developing the DL model. We used a realistic set of assumptions to estimate the VLV for the future time steps for the range of allowable speed values and applied them at the input of the developed DL model to generate multiple sets of EOP’s. We imposed the defined EOC criteria on these EOPs, and the top three modes of speeds satisfying all the requirements are derived at each second. Thus, three eligible speed values are estimated for each second, and an additional criterion is defined to generate a unique ACCSSP for future time steps. A performance comparison between predicted and constant ACCSSP’s indicates that the predictive model outperforms constant ACCSSP.
Operating point
Model Predictive Control
Operating speed
Constant (computer programming)
Feature (linguistics)
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The use of Model Predictive Control (MPC) is commonplace in many industrial applications. The anticipative nature of MPC and the inclusion of physical constraints into the control framework presents many advantages over classical control strategies. Despite these advantages, obtaining an accurate open-loop model of the underlying process is often a difficult and time consuming process. In this paper, a methodology is introduced to identify linear open-loop models of gas turbine engines from closed-loop data. The closed-loop data can be obtained by any sufficiently informative experiment from a plant in operation or simulation. We present simulation results here. These open-loop models are then used in the design of model predictive controllers at a number of operating points of the turbine. The predictive controllers we designed include physical constraints on the fuel and air flow into the turbine. The performance of these predictive controllers is compared in simulation against existing classical control techniques in a number of typical operating scenarios including off loads, on loads and set point changes.
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Open-loop controller
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Loss modelling for induction machines operated as variable speed drives (VSD) is indispensable for designing highly utilised traction machines. Accurate loss modelling can be performed using finite-element analysis (FEA). Since VSD have to deliver torque at different values of mechanical speed, the torque-speed operating points are sought. For those torque-speed operating points, the drive should be operated in the highest efficiency points. Finding these points from transient FEA requires the simulation of several ten to hundreds operating points in terms of stator current and rotor fundamental frequency. For that reasons, local loss modelling using FEA is very time consuming. This study will present a hybrid simulation approach coupling numerical and analytical models to reduce simulation time for simulation of the torque-speed operating points. The simulation approach takes into account the inverter voltage and current limitations and finds the highest efficiency operating point for every torque-speed operating point.
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Operating speed
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Model Predictive Control (MPC) offers a variety of advantages compared to conventional control methods. A MPC includes a process model of the system to be controlled. Based on this model the controller determines the optimal actuating variable for future timesteps in every sampling step. In this paper a Direct Torque Model Predictive Control (DT-MPC) method for nonlinear systems with inherent output saturation is presented. This approach offers real-time capability for online MPC even for processes with time constants in the millisecond range. Furthermore, it is shown in this paper, how the optimization algorithm in the MPC can be used in order to achieve optimized efficiency of interior permanent magnet synchronous motors (IPMSM). Using the results of simulation the good control performance as well as the optimization of the efficiency of an electrical drive train can be shown. Thus, the DT-MPC provides maximum torque per current (MTPC) operating currents without the need of additional operating point choice.
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According to the influence of operating speed,this article sets up kinds of theoretical operating speed model,in order to apply to straight line,easement curve and circular curve.At the same time,we study on critical radius and obtain the maximal steady theoretical operating speed in different design speed,and can provide the basis for theoretical operating speed,dividing into sections and integrating models.
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Operating point
Easement
Critical speed
Design speed
Speedup
Line (geometry)
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SIGNAL (programming language)
Operating point
Rolling-element bearing
Test bench
Operating speed
Condition Monitoring
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The stability of adaptive full-order observer (AFO) can be improved by feedback gain tuning and speed adaptive scheme modification for sensorless induction motor (IM) drives in low-speed regenerating mode. However, few research concern this problem with attention to IM operating point changes. To cope with this problem, this paper proposes an operating-point tracking method to design feedback gain and speed adaptive scheme for AFO. Compared with the existing approaches, lower synchronous speed can be accessible during step speed and load changes in low-speed regenerating mode without signal injection. Addressing the operating point changes, the estimated flux error is derived by adapting the projection of estimated current error with respect to speed and torque. The derivative estimated flux error with changing parameters is taken as an additional variable to design feedback gain. Meanwhile, the speed adaptive scheme is modified by the operating-point tracking expression. As a result, the proposed method acquires the capacity to track the operating point in real time. The experimental results on a 2.2-kW IM experimental setup confirm the effectiveness of the proposed method.
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Observer (physics)
Operating speed
Mode (computer interface)
Tracking error
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Abstract This paper addresses the stability of traffic flow on a highway when the vehicles operate under an adaptive cruise control (ACC) system. ACC systems are commonly designed to maintain a constant time-gap between vehicles during vehicle following. Previous researchers in literature have produced contradictory results on whether the traffic flow is stable when the constant time gap spacing policy is used. This paper resolves the contradiction and shows that the boundary conditions used at the inlets and exits influence traffic flow stability in the case of the constant time-gap policy. Further, the paper shows that it is possible to design an unconditionally stable spacing policy, i.e. a spacing policy which guarantees traffic stability under all boundary conditions. The practical implications of instability are shown through traffic simulation results. The advantages of an unconditionally stable spacing policy over the constant time-gap policy are demonstrated. The answer to the question “Should ACC systems be designed to maintain a constant time gap between vehicles?” is NO. It is quite easy to develop alternate spacing policies with superior stability properties.
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Time constant
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It cannot always be said that applying varlable speed drives to parallel operation fans are the best choice or the most cost-effective. Depending on the conditions of operating and drive capacity, the vane - speed control will be more favorable than others. In this case, there are lots of combination operating points between the vane opening and the fan speed. The efficiency optimal operating point for a vane - speed parallel fan system is calculated and tested to the forced draft fans in a power plant boiler The results ascertain the validity of the theoretical analysis.
Operating point
Operating speed
Electronic speed control
Operating cost
Flow Control
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