Integrated computational intelligent paradigm for nonlinear electric circuit models using neural networks, genetic algorithms and sequential quadratic programming

© 2019, Springer-Verlag London Ltd., part of Springer Nature. In this paper, a novel application of biologically inspired computing paradigm is presented for solving initial value problem (IVP) of electric circuits based on nonlinear RL model by exploiting the competency of accurate modeling with feed forward artificial neural network (FF-ANN), global search efficacy of genetic algorithms (GA) and rapid local search with sequential quadratic programming (SQP). The fitness function for IVP of associated nonlinear RL circuit is developed by exploiting the approximation theory in mean squared error sense using an approximate FF-ANN model. Training of the networks is conducted by integrated computational heuristic based on GA-aided with SQP, i.e., GA-SQP. The designed methodology is evaluated to variants of nonlinear RL systems based on both AC and DC excitations for number of scenarios with different voltages, resistances and inductance parameters. The comparative studies of the proposed results with Adam’s numerical solutions in terms of various performance measures verify the accuracy of the scheme. Results of statistics based on Monte-Carlo simulations validate the accuracy, convergence, stability and robustness of the designed scheme for solving problem in nonlinear circuit theory

Study and modelling of lithium ion cell with accurate soc measurement algorithm using Kalman filter for electric vehicles

Lithium Ion cells are preferred over lead acid cells for electric vehicles due to their energy density, higher discharge current and size. The cost of lithium ion cells is scaling down compared to ten years earlier, but as their performance characteristics increase, the need for safety and accurate modelling also increases. The absence of a generic cell model is associated to the different makes of cells and different chemistries of Lithium ion cells behave differently under the testing conditions required for every unique application. The focus of this thesis will be on how to provide intelligence to the battery management system for calculating the state of charge of a cell so that the depth of discharge of the pack can be controlled, and to balance the voltage levels of all modules in a battery pack. This will involve cycling of the chosen type of cell, modelling it for its parameters, analyzing the cycling data and choosing the perfect depth of discharge required for the application from the energy or capacity vs open circuit voltage (OCV) graph. The lithium ion model will be evaluated from the transient response of the battery pack. This will then be made as a working prototype on an electric vehicle car and its behavior studied practically

System level performance and yield optimisation for analogue integrated circuits

Advances in silicon technology over the last decade have led to increased integration of analogue and digital functional blocks onto the same single chip. In such a mixed signal environment, the analogue circuits must use the same process technology as their digital neighbours. With reducing transistor sizes, the impact of process variations on analogue design has become prominent and can lead to circuit performance falling below specification and hence reducing the yield.This thesis explores the methodology and algorithms for an analogue integrated circuit automation tool that optimizes performance and yield. The trade-offs between performance and yield are analysed using a combination of an evolutionary algorithm and Monte Carlo simulation. Through the integration of yield parameter into the optimisation process, the trade off between the performance functions can be better treated that able to produce a higher yield. The results obtained from the performance and variation exploration are modelled behaviourally using a Verilog-A language. The model has been verified with transistor level simulation and a silicon prototype.For a large analogue system, the circuit is commonly broken down into its constituent sub-blocks, a process known as hierarchical design. The use of hierarchical-based design and optimisation simplifies the design task and accelerates the design flow by encouraging design reuse.A new approach for system level yield optimisation using a hierarchical-based design is proposed and developed. The approach combines Multi-Objective Bottom Up (MUBU) modelling technique to model the circuit performance and variation and Top Down Constraint Design (TDCD) technique for the complete system level design. The proposed method has been used to design a 7th order low pass filter and a charge pump phase locked loop system. The results have been verified with transistor level simulations and suggest that an accurate system level performance and yield prediction can be achieved with the proposed methodology

Lithium-sulfur cell equivalent circuit network model parameterization and sensitivity analysis

Compared to lithium-ion batteries, lithium-sulfur (Li-S) batteries potentially offer greater specific energy density, a wider temperature range of operation, and safety benefits, making them a promising technology for energy storage systems especially in automotive and aerospace applications. Unlike lithium-ion batteries, there is not a mature discipline of equivalent circuit network (ECN) modelling for Li-S. In this study, ECN modelling is addressed using formal ‘system identification’ techniques. A Li-S cell’s performance is studied in the presence of different charge/discharge rates and temperature levels using precise experimental test equipment. Various ECN model structures are explored, considering the trade-offs between accuracy and speed. It was concluded that a ‘2RC’ model is generally a good compromise, giving good accuracy and speed. Model parameterization is repeated at various state-of-charge (SOC) and temperature levels, and the effects of these variables on Li-S cell’s ohmic resistance and total capacity are demonstrated. The results demonstrate that Li-S cell’s ohmic resistance has a highly nonlinear relationship with SOC with a break-point around 75% SOC that distinguishes it from other types of battery. Finally, an ECN model is proposed which uses SOC and temperature as inputs. A sensitivity analysis is performed to investigate the effect of SOC estimation error on the model’s accuracy. In this analysis, the battery model’s accuracy is evaluated at various SOC and temperature levels. The results demonstrate that the Li-S cell model has the most sensitivity to SOC estimation error around the break-point (around 75% SOC) whereas in the middle SOC range, from 20% to 70%, it has the least sensitivity

A Review of Optimization Approach to Power Flow Tracing in a Deregulated Power System

Power Flow Tracing (PFT) is known to be the best method in the allocation of charges to users of transmission systems, generators and loads, in a deregulated environment. The optimization approach to PFT produced better results than other methods because it considers the physical power flow results and electrical constraints of the system. A brief review of the optimal power flow concept, PFT techniques, and the deterministic and non-deterministic optimization methods applied to PFT are presented. The paper also highlighted the future trends of hybrid optimization approach to PFT. It is recommended that more research work should be directed on the hybrid optimization methods to solve PFT problems

Multiphysics Simulation and Model-based System Testing of Automotive E-Powertrains

Programa Oficial de Doutoramento en Enxeñaría Naval e Industrial . 5015V01[Abstract] Model-Based System Testing emerges as a new paradigm for the development cycle that is currently gaining momentum, especially in the automotive industry. This novel approach is focused on combining computer simulation and real experimentation to shift the bulk of problem detection and redesign tasks towards the early stages of the developments. Along these lines, Model-Based System Testing is aimed at decreasing the amount of resources invested in these tasks and enabling the early identification of design flaws and operation problems before a full-vehicle prototype is available. The use of Model-Based System Testing, however, requires to implement some critical technologies, three of which will be discussed in this thesis. The first task addressed in this thesis is the design of a multiplatform framework to assess the description and resolution of the equations of motion of virtual models used in simulation. This framework enables the efficiency evaluation of different modelling and solution methods and implementations. In Model-Based System Testing contexts virtual models interact with physical components, therefore it is mandatory to guarantee their real-time capabilities, regardless of the software or hardware implementations. Second, estimation techniques based on Kalman Filters are of interest in Model- Based System Testing applications to evaluate parameters, inputs or states of a virtual model of a given system. These procedures can be combined with the use of Digital Twins, virtual counterparts of real systems, with which they exchange information in a two-way communication. The available measurements from the sensors located at a physical system can be fused with the results obtained from the simulation of the virtual model. Thus, this avenue improves the knowledge of the magnitudes that cannot be measured directly by these sensors. In turn, the outcomes obtained from the simulation of the virtual model could serve to make decisions and apply corrective actions onto the physical system. Third, co-simulation techniques are necessary when a system is split into several subsystems that are coordinated through the exchange of a reduced set of variables at discrete points in time. This is the case with a majority of Model-Based System Testing applications, in which physical and virtual components are coupled through a discrete-time communication gateway. The resulting cyber-physical applications are essentially an example of real-time co-simulation, in which all the subsystems need to achieve real-time performance. Due to the presence of physical components, which cannot iterate over their integration steps, explicit schemes are often mandatory. These, however, introduce errors associated with the inherent delays of a discrete communication interface. These errors can render co-simulation results inaccurate and even unstable unless they are eliminated. This thesis will address this correction by means of an energy-based procedure that considers the power exchange between subsystems. This research work concludes with an example of a cyber-physical application, in which real components are interfaced to a virtual environment, which requires the application of all the MBST technologies addressed in this thesis.[Resumen] Los ensayos de sistemas basados en modelos emergen como un nuevo paradigma de desarrollo que actualmente está ganando popularidad, especialmente en la industria automotriz. Este nuevo enfoque se centra en combinar la simulación por ordenador con la experimentación para desplazar la mayor parte de la detección de problemas y rediseños hacia las fases tempranas del desarrollo. De esta forma, los ensayos de sistemas basados en modelos se centran en disminuir la cantidad de recursos invertidos en estas tareas y habilitar la identificación temprana de errores de diseño y problemas durante la operación, incluso antes de que los prototipos del vehículo completo estén disponibles. Sin embargo, el uso de esta estrategia requiere implementar algunas tecnologías críticas, tres de las cuales serán tratadas en esta tesis. La primera tarea abordada en esta tesis es el diseño de un entorno multiplataforma para evaluar la descripción y resolución de las ecuaciones de la dinámica de los modelos virtuales usados en las simulaciones. Este marco permite una evaluación eficiente de las diferentes formas de modelar los sistemas y de los métodos de resolución e implementación. En este contexto de ensayos basados en modelos, los sistemas virtuales interactúan con los componentes de los sistemas físicos, por lo tanto es necesario garantizar sus capacidades de ejecución en tiempo real, independientemente de la plataforma de software y hardware utilizada. En segundo lugar, las técnicas de estimación basadas en filtros de Kalman son de gran interés en las aplicaciones que usan ensayos basados en modelos para evaluar los parámetros, entradas o estados de los modelos virtuales de un sistema dado. Estos procedimientos se pueden combinar con el uso de gemelos digitales, homólogos virtuales de un sistema físico, con el cual mantienen un flujo bidireccional de intercambio de información. Las medidas disponibles procedentes de los sensores instalados en un sistema físico se pueden combinar con los resultados obtenidos de la simulación del sistema virtual. De este modo, este enfoque mejora el conocimiento de las magnitudes que no pueden ser medidas directamente por los sensores. A su vez, los resultados de la simulación de los sistemas de los modelos virtuales pueden servir para tomar decisiones y aplicar medidas correctivas al sistema real. En tercer lugar, las técnicas de co-simulación son necesarias cuando un sistema se divide en varios subsistemas, coordinados a través del intercambio de un reducido número de variables en momentos puntuales. Este es el caso de la mayor parte de las aplicaciones que siguen la estrategia de ensayos basados en modelos, en los cuales los componentes físicos y virtuales se acoplan mediante una comunicación en tiempo discreto. Como resultado las aplicaciones ciberfísicas son en esencia un ejemplo de co-simulación en tiempo real, en la que todos los subsistemas necesitan cumplir los requisitos de ejecución en tiempo real. Debido a la presencia de componentes físicos, que no pueden reiterar sus pasos de integración, el uso de esquemas explícitos es frecuentemente necesario. Sin embargo, estos esquemas introducen errores asociados con los retrasos propios de una interfaz de tiempo discreto. Estos errores pueden dar lugar a resultados erróneos e incluso inestabilizar la co-simulación, si no son eliminados. Esta tesis aborda la corrección de la co-simulación a través de métodos energéticos basados en la potencia intercambiada por los subsistemas. Este trabajo de investigación concluye con un ejemplo de aplicación ciberfísica, en la que se conectan componentes reales a una simulación por ordenador. Esta aplicación requiere la aplicación de las tecnologías de ensayos basados en modelos presentadas a lo largo de esta tesis.[Resumo] Os ensaios de sistemas baseados en modelos xorden como un novo paradigma de desenvolvemento que actualmente está gañando popularidade, especialmente na industria automotriz. Este novo enfoque céntrase en combinar a simulación por ordenador coa experimentación para desprazar a maior parte da detección de problemas e redeseños cara as fases iniciais do ciclo de produto. Deste xeito, os ensaios de sistemas baseados en modelos fundaméntanse en diminuír a cantidade de recursos investidos nestas tarefas e habilitar a identificación temperá de erros de deseño e problemas durante a operación, aínda se os prototipos do vehículo completo non están dispoñibeis. Porén, o uso desta estratexia require implementar algunhas tecnoloxías críicas, tres das cales serán tratadas nesta tese. A primeira tarefa tratada nesta tese é o deseño dun entorno multiplataforma para avaliar a descripción e resolución das ecuacións da dinámica dos modelos virtuais empregados nas simulacións. Este entorno permite unha avaluación eficiente dos diferentes xeitos de modelar os sistemas e dos métodos de resolución e implementación. Neste contexto de ensaios baseados en modelos, os sistemas virtuais interactúan cos compoñentes dos sistemas físicos, polo tanto é necesario garantir as súas capacidades de execución en tempo real, independentemente da plataforma de hardware e software escollida. En segundo lugar, as técnicas de estimación baseadas en filtros de Kalman son de grande interese nas aplicacións que usan ensaios baseados en modelos para avaliar os seus parámetros, entradas ou estados dos modelos virtuais dun certo sistema. Estes procedementos pódense combinar co uso de xemelgos dixitais, homólogos virtuais dun sistema físico, co cal manteñen un fluxo bidireccional de intercambio de información. As medidas dispoñíbeis procedentes dos sensores instalados nun sistema físico pódense combinar cos resultados obtidos da simulación do sistema virtual. Deste xeito, este enfoque mellora o coñecemento das magnitudes que non poden ser medidas directamente polos sensores. Á súa vez, os resultados da simulación dos sistemas dos modelos virtuais poden servir para tomar decisións e aplicar medidas correctivas ao sistema real. En terceiro lugar, as técnicas de co-simulación son necesarias cando un sistema é dividido en varios subsistemas, coordinados a través do intercambio dun reducido número de variables en momentos puntuais. Este é o caso da maior parte das aplicacións que seguen a estratexia de ensaios baseados en modelos, nos cales os compoñentes físicos e virtuais se acoplan mediante unha comunicación en tempo discreto. Como resultado as aplicacións ciberfísicas son esencialmente un exemplo de co-simulación en tempo real, na que tódolos subsistemas necesitan cumprir os requisitos de execución en tempo real. Debido á presenza de compoñentes físicos, que non poden reiterar os seus pasos de integración, o uso de esquemas explícitos é polo xeral necesario. Con todo, estes esquemas introducen erros asociados cos atrasos derivados dunha interface de tempo discreto. Estes erros poden provocar resultados incorrectos e incluso inestabilizar a co-simulación, de non seren eliminados. Esta tese aborda a corrección da co-simulación a través de métodos enerxéticos baseados na potencia intercambiada polos subsistemas. Este traballo conclúe cun exemplo de aplicación ciberfísica, na que os compoñentes reais son conectados a un entorno virtual. Isto require o emprego de tódalas tecnoloxías de ensaios baseadas en modelos presentadas ao longo desta tese