Control algorithms for e-car

Cílem práce byl návrh a implementace řídicích algoritmů pro optimalizaci spotřeby energie elektrického vozidla. Hlavním úkolem byla optimalizace rozložení energie mezi hlavním zdrojem energie (bateriemi) a super-kapacitory v průběhu jízdního cyklu. Jízdní výkonový profil je odhadován a předpovězen na základě 3D geografických souřadnic a matematického modelu vozidla. V první části jsou uvedeny komponenty vozidla a jejich modely. Poté jsou představeny algoritmy na základě klouzavého průměru a dynamického programování. Byly provedeny simulace a analýzy pro demostraci přínosů algoritmů. V poslední části je popsána Java implementace algoritmů a také aplikace pro operační systém Android.The aim of this work is to design and implement energy consumption optimization control algorithms for electric vehicle. The main objective is to optimize the power-split-ratio between the main power source (batteries) and the super-capacitors during the driving cycle. The driving power profile is estimated and predicted using 3D geographic data and vehicle model. In the first part, vehicle components modelling is introduced. Then, moving average based algorithm and dynamic programming algorithm are presented. Simulations and analysis are provided to show algorithms' benefits. In the last part, Java implementation and also Android operating system application are described.

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Three-phase modular permanent magnet brushless machine for torque boosting on a downsized ICE vehicle

The paper describes a relatively new topology of 3-phase permanent magnet (PM) brushless machine, which offers a number of significant advantages over conventional PM brushless machines for automotive applications, such as electrical torque boosting at low engine speeds for vehicles equipped with downsized internal combustion engine (ICEs). The relative merits of feasible slot/pole number combinations for the proposed 3-phase modular PM brushless ac machine are discussed, and an analytical method for establishing the open-circuit and armature reaction magnetic field distributions when such a machine is equipped with a surface-mounted magnet rotor is presented. The results allow the prediction of the torque, the phase emf, and the self- and mutual winding inductances in closed forms, and provide a basis for comparative studies, design optimization and machine dynamic modeling. However, a more robust machine, in terms of improved containment of the magnets, results when the magnets are buried inside the rotor, which, since it introduces a reluctance torque, also serves to reduce the back-emf, the iron loss and the inverter voltage rating. The performance of a modular PM brushless machine equipped with an interior magnet rotor is demonstrated by measurements on a 22-pole/24-slot prototype torque boosting machine

Modeling and simulation enabled UAV electrical power system design

With the diversity of mission capability and the associated requirement for more advanced technologies, designing modern unmanned aerial vehicle (UAV) systems is an especially challenging task. In particular, the increasing reliance on the electrical power system for delivering key aircraft functions, both electrical and mechanical, requires that a systems-approach be employed in their development. A key factor in this process is the use of modeling and simulation to inform upon critical design choices made. However, effective systems-level simulation of complex UAV power systems presents many challenges, which must be addressed to maximize the value of such methods. This paper presents the initial stages of a power system design process for a medium altitude long endurance (MALE) UAV focusing particularly on the development of three full candidate architecture models and associated technologies. The unique challenges faced in developing such a suite of models and their ultimate role in the design process is explored, with case studies presented to reinforce key points. The role of the developed models in supporting the design process is then discussed

Fault estimation and fault-tolerant control for discrete-time dynamic systems

In this paper, a novel discrete-time estimator is proposed, which is employed for simultaneous estimation of system states, and actuator/sensor faults in a discrete-time dynamic system. The existence of the discrete-time simultaneous estimator is proven mathematically. The systematic design procedure for the derivative and proportional observer gains is addressed, enabling the estimation error dynamics to be internally proper and stable, and robust against the effects from the process disturbances, measurement noise, and faults. Based on the estimated fault signals and system states, a discrete-time fault-tolerant design approach is addressed, by which the system may recover the system performance when actuator/sensor faults occur. Finally, the proposed integrated discrete-time fault estimation and fault-tolerant control technique is applied to the vehicle lateral dynamics, which demonstrates the effectiveness of the developed techniques

Fiscal year 1973 scientific and technical reports, articles, papers, and presentations

Formal NASA technical reports, papers published in technical journals, and presentations by MSFC personnel in FY73 are presented. Papers of MSFC contractors are also included

Modeling and Control for Smart Grid Integration of Solar/Wind Energy Conversion System

Performance optimization, system reliability and operational efficiency are key characteristics of smart grid systems. In this paper a novel model of smart grid-connected PV/WT hybrid system is developed. It comprises photovoltaic array, wind turbine, asynchronous (induction) generator, controller and converters. The model is implemented using MATLAB/SIMULINK software package. Perturb and observe (P&O) algorithm is used for maximizing the generated power based on maximum power point tracker (MPPT) implementation. The dynamic behavior of the proposed model is examined under different operating conditions. Solar irradiance, temperature and wind speed data is gathered from a grid connected, 28.8kW solar power system located in central Manchester. Real-time measured parameters are used as inputs for the developed system. The proposed model and its control strategy offer a proper tool for smart grid performance optimization