1,720,975 research outputs found
Hybrid modelling and control for switched-mode power converters
No full textSwitched-mode power converters are some of the most widely used power electronics circuits due to their advantages of high conversion efficiency, flexible output voltage, light weight. A variety of control methods have been developed for the switched-mode power converters. However, in many practical situation, additional constraints need to be considered, e.g., safety measurement, current limiting or soft-starting, gross changes of operation point with guaranteed system stability, which has not been fully addressed in the available research works. On the other hand, the majority of the control design for power converters are based on the state-space averaged approach which involves considerable approximation in analysis and synthesis. Hence, advanced control techniques are in demand, which should be more constraints friendly and based on more precise models.In this thesis, much attention has been spent on designing controllers for both DC-DC converters and DC-AC inverters based on hybrid modelling and Lyapunov stability theory. Due to the existence of the power switches, switched-mode power converters are hybrid systems with both continuous dynamics and discrete transition events. Instead of linearizing the converter model around a specific operating point, hybrid modelling captures both dynamics, which results in more accurate models.Firstly, a novel sampled-data control approach is proposed for DC-DC converters. DC-DC converters are modeled as sampled-data switched affine systems according to the status of the power switch. In order to avoid the delay of the switching signal, an on-line prediction method is adopted to estimate the system state at the next switching instant. Based on the switched affine model and the predicted system state, a novel switching control algorithm is synthesized by using the switched Lyapunov theory. The proposed approach is able to not only drive the output to a prescribed set point from any initial condition, but also track a varying reference signal, and the switching frequency can be adjusted online with guaranteed stability. In addition, with this approach, Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) operations can be treated in a unified way. Experimental verification has been carried out to test the effectiveness and merits of the proposed method.Furthermore, to compensate the information loss due to limited access to the state, a multiple sampling scheme is employed to derive a discrete-time switched affine model with an augmented measurement output for DC-DC converters. Based on the model, an output-feedback switching control law, which drives the system state to a set of attainable switched equilibria, is synthesized by using a quadratic state-space partition. The multiple sampling scheme not only facilitates the controller synthesis, but also improves the energy efficiency of the converter by allowing a lower switching frequency.In addition, hybrid modelling techniques have been extended to more complicated cases – DC-AC inverters as the increasing number of power switches and the time-variant nature of the references. A current controller based on the hybrid model of the three-phase two-level inverter has been developed, which can drive the inverter currents tracking the desired power references in realtime and keep a unity power factor at the same time. This method has been extended to three-phase NPC inverters later on. However, in order to solve the neutral point balancing issue, a capacitor voltages prediction algorithm, modified from model predictive control, has been adopted. It should also be mentioned that a novel hybrid model for a grid-connected single-phase NPC inverter also has been presented, which models not only the dynamic of the inverter but also the dynamic of the current reference. An experimental test platform including a three-phase NPC inverter and a FPGA control board has been designed to demonstrate the implementation of the proposed control scheme in practice
A/C energy management and vehicle cabin thermal comfort control
No full textThis paper introduces a novel multi-objective controller which regulates A/C system operation in a trade-off between vehicle cabin comfort and fuel consumption for a conventional vehicle with internal combustion engine. The controller has been developed and tested in a simulated environment, where an energy-based model of the A/C system is combined with a thermal dynamic model of the cabin which considers heat transfer to the environment. The control algorithm proposed herein is compared with two widely used control techniques in the industry, respectively the thermostat and PI control, under different driving cycles. This novel method is implementable in real-time, and simulation results show a reduction of up to 2% in A/C system fuel consumption compared to existing methods with similar thermal performance
A/C Energy Management and Vehicle Cabin Thermal Comfort Control
Full text linkThis paper introduces a novel multi-objective controller which regulates A/C system operation in a trade-off between vehicle cabin comfort and fuel consumption for a conventional vehicle with internal combustion engine. The controller has been developed and tested in a simulated environment, where an energy-based model of the A/C system is combined with a thermal dynamic model of the cabin which considers heat transfer to the environment. The control algorithm proposed herein is compared with two widely used control techniques in the industry, respectively the thermostat and PI control, under different driving cycles. This novel method is implementable in real-time, and simulation results show a reduction of up to 2% in A/C system fuel consumption compared to existing methods with similar thermal performance
Extending the range of Plug-in Hybrid Electric Vehicles by CVT transmission optimal management
No full textDue to the ability to obtain energy from direct connection to the electricity grid, plug-in hybrid electric vehicles benefit both society and drivers environmentally and economically by reducing energy consumption and emissions. To extend the travel range, existing studies focus mostly on optimizing the power split of the internal combustion engine and battery without considering the impact of the transmission system. This paper deals with the optimization of a continuously variable transmission (CVT) operation for a parallel pre-transmission hybrid powertrain. The novelty of this paper is that the operation of both engine and CVT transmission are optimized together, resulting in a better fuel efficiency. Simulation work has been carried out to compare the performance of the optimized CVT transmission with a fixed transmission, showing that the fuel consumption is reduced and hence the range is increased for the optimized CVT, which makes the engine to operate in higher efficiency points. A key advantage of the formulation proposed is that the result of the optimization process may be expressed in terms of a 2D map that for any pair of vehicle speed and traction force gives the optimal value of the CVT transmission ratio. Such a map may be easily implemented in real vehicular applications
Driver modeling and implementation of a fuel-saving ADAS
No full textControlling vehicle velocity, by coaching the driver to eco-drive with an advanced driver assistance system (ADAS), is a promising method to decrease fuel consumption and greenhouse gas emissions for combustion engine-driven road vehicles. By using optimal control techniques, such a system may find velocity profiles in real-time that minimize fuel consumption. This is particularly useful to recommend the optimal time to initiate coasting, which is otherwise difficult to estimate by a driver. However, this ADAS should not choose velocities and accelerations that the driver will dislike, such as those that leave too much or too little space to the preceding vehicle, or those that take corners at high speed. To remedy this, we introduce an optimal control model of acceleration that mimics drivers' behavior and combine this with a model of fuel consumption to trade-off driver preferences and fuel savings. We give examples of the velocity profiles recommended in a typical driving scenario to demonstrate the potential fuel savings. Finally, we give details of a prototype system, which has recently been implemented in the driving simulator at the University of Southampton
Adaptive driver modelling in ADAS to improve user acceptance: a study using naturalistic data
No full textAccurate understanding of driver behaviour is crucial for future Advanced Driver Assistance Systems (ADAS) and autonomous driving. For user acceptance it is important that ADAS respect individual driving styles and adapt accordingly. Using data collected during a naturalistic driving study carried out at the University of Southampton, we assess existing models of driver acceleration and speed choice during car following and when cornering. We observe that existing models of driver behaviour that specify a preferred inter-vehicle spacing in car-following situations appear to be too prescriptive, with a wide range of acceptable spacings visible in the naturalistic data. Bounds on lateral acceleration during cornering from the literature are visible in the data, but appear to be influenced by the minimum cornering radii specified in design codes for UK roadway geometry. This analysis of existing driver models is used to suggest a small set of parameters that are sufficient to characterise driver behaviour in car-following and curve driving, which may be estimated in real-time by an ADAS to adapt to changing driver behaviour. Finally, we discuss applications to adaptive ADAS with the objectives of improving road safety and promoting eco-driving, and suggest directions for future research
Incorporating Driver Preferences Into Eco-Driving Assistance Systems Using Optimal Control
Full text linkRecently there have been several proposals for `eco-driving assistance systems', designed to save fuel or electrical power by encouraging behaviours such as gentle acceleration and coasting to a stop. These systems use optimal control to find driving behaviour that minimises vehicle energy losses. In this paper, we introduce a methodology to account for driver preferences on acceleration, braking, following distances and cornering speed in such eco-driving optimal control problems. This consists of an optimal control model of acceleration and braking behaviour containing several physically-meaningful parameters to describe driver preferences. If used in combination with a model of fuel or energy consumption, this can provide an adjustable trade-off between satisfying those preferences and minimising energy losses. We demonstrate that the model gives comparable performance to existing car-following and cornering models when predicting drivers' speed in these situations by comparison with real-world driving data. Finally, we present an example highway braking scenario for an electric vehicle, illustrating a trade-off between satisfying driver preferences on vehicle speed and acceleration and reducing electrical energy usage by up to 43
Fuel Economy and Naturalistic Driving for Passenger Road Vehicles
No full textThe state-of-the-art eco-driving techniques does not
take into account the naturalistic behaviour of human drivers.
Therefore, in this paper, a unified driver model is proposed
which describes the driver preference during car following and
cornering cases. The model is formulated based on the optimal
control theory. The fuel consumption model of a traditional
vehicle with an internal combustion (IC) engine and CVT
transmission is combined with the driver model. The proposed
optimal controller is designed to generate speed profile and
powertrain inputs, which give a compromise between the driver
preference and fuel economy. The simulation results demonstrate
that eco-friendly speed profile and optimal powertrain input
trajectories could be selected which has good fuel economy and
matches the driver desires
Inception, ideation and implementation: developing interfaces to improve drivers’ fuel efficiency
No full textCognitive Work Analysis has become a staple methodology for Human Factors and Ergonomics researchers and practitioners. Despite this popularity, limited guidance is available to take the insights of the methodology forward into the development of newer systems and interfaces. This paper describes the use of the established design toolkit “Design with Intent” as a suitable approach to help progress the insights of Cognitive Work Analysis towards the development of novel interfaces. An abridged account of developing a Cognitive Work Analysis for fuel efficient driving is presented, alongside the application of the Design with Intent toolkit to progress the insights from the Cognitive Work Analysis to generate novel design ideas which can be incorporated into future interfaces. Finally, early development work, compiling the ideas generated using the Design with Intent toolkit, is presented, demonstrating the potential for this combination of methods to produce interfaces for future testing and validation
Sampled-data control with adjustable switching frequency for DC-DC converters
No full textIn this paper, a novel sampled-data control approach is proposed for DC-DC converters. The DC-DC power electronic converter is modeled as a sampled-data switched affine systems according to the status of the power switch. A novel switching control algorithm is synthesized by using the switched Lyapunov theory. The proposed approach is able to not only drive the output to a prescribed set point from any initial condition but also track a varying reference signal, and the switching frequency can be adjusted online with guaranteed stability. In addition, with this approach, CCM and DCM operations can be treated in a unified way. The effectiveness and merits of the proposed method are illustrated by experiments on a laboratory prototype
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