Prognostic Reasoner based adaptive power management system for a more electric aircraft

This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled.A hybrid mathematical model based on the Direct-Quadrature (d-q) axis transformation of the generator have been formulated for studying various structural and parametric faults. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study were carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been develope

Temperature-Dependent Thévenin Model of a Li-Ion Battery for Automotive Management and Control

This paper focuses on the analysis of Li-ion battery behavior at different temperatures through the Thévenin electrical circuit model. First, evaluations for both steady-state and dynamic battery applications are provided, then an overview of the different battery models to describe their dynamic behavior is analyzed. The focus is dedicated to the double polarization Thévenin-based equivalent circuit model since it represents an optimal trade-off between accuracy and computation effort, which justifies its implementation in a Battery Management System (BMS) for automotive real-time monitoring and control. The model is composed of a voltage source, one series resistor and two series RC blocks. The Hybrid Pulse Power Characterization test (HPPC) is performed inside a climatic chamber to extract the electrical parameters of the model and their dependency from both temperature and State Of Charge (SOC). The load-current effects on the battery performance are not considered for the simplicity and lightness of the presented model. The presented procedure has broader validity and is mostly independent of cell format and Li-ion chemistry, despite a specific cylindrical battery cell is chosen for the study. The results of the test are suitable for the future implementation of a proper algorithm for SOC and State Of Health SOH estimations. Moreover, they provide an effective electrical and thermal characterization of the cell to evaluate the heat generation rate inside the cell

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

COMPREHENSIVE THERMAL MODELING OF POWER SPLIT HYBRID POWER-TRAIN AND ELECTRONICS

Hybrid electric vehicle (HEV) uses both internal combustion engine (ICE) with an electric system. The combination of the electric power train with the ICE is intended to achieve both better fuel economies than the conventional vehicles and better performance. Several types of HEV exist with different layouts. Recent HEVs\u27 make use of regenerative braking, which converts the vehicles\u27 kinetic energy into electric energy instead of wasting it as heat as conventional brakes do. A hybrid-electric is more fuel efficient than ICE and has less environmental impact. The new HEV with its new Key Characteristics and Configurations (i.e. Mechanical complexity, Multiple driving modes, Multiple prime movers, ... etc) inflict an interference with the existed thermal management system of the conventional vehicles, which leads to a new thermal management issues that should be addressed to enhance the performance of such systems. There is no complete knowledge in the open literature about the thermal management issues of HEV yet. This dissertation introduces Comprehensive Thermal Modeling of Hybrid Vehicular systems to assist monitoring the added-on of hybrid modules into the vehicle thermal management system. The model proposes a combined experimental and finite differencing nodal net work simulation modeling approach; using Thermography detectors calibrated for emissivity to capture 2-D spatial and transient temperature measurements. The Thermographic detectors were deployed through dual band thermography to neutralize the emissivity and to provide different dynamic ranges to iii achieve accurate temperature measurements. A thermocouples network was installed to provide a reference signal. A new comprehensive 3-D thermal model was developed by generating 3-D surface description for a complete hybrid electric vehicle from 3-D scans of an actual vehicle to guarantee the quality of the surface geometry, and break down the surfaces of the model into finite elements to improve the accuracy for better thermal analysis. The boundary conditions from a vehicle under different driving modes and load scenarios were deployed into the finite differencing simulation which was performed using finite differencing code capable of solving a sophisticated thermal/fluid systems with minimal user interaction (RadTherm) to provide a 3-D Thermal predictions and an Image Viewer (wireframe and animated thermal display). The 3-D model assisted monitoring the adding of Hybrid modules into the vehicle thermal management system and was used to analyze packaging considerations and integrating different modules for Hybrid Vehicles. In addition to the design of alternative materials for hybrid modules and Battery Packs for better thermal management; the model assisted studying the influence of applying different cooling methodologies and evaluate its effect on the thermal performance of the HEVs\u27 power trains. A spatial and a transient temperature profiles obtained from the simulation for different components were compared with experimental results in order to validate the complete thermal model

Automotive Powertrain Control — A Survey

This paper surveys recent and historical publications on automotive powertrain control. Control-oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72023/1/j.1934-6093.2006.tb00275.x.pd