Unified backwards facing and forwards facing simulation of a hybrid electric vehicle using MATLAB Simscape

This paper presents the implementation of a vehicle and powertrain model of the parallel hybrid electric vehicle which can be used for several purposes: as a model for estimating fuel consumption, as a model for estimating performance, and as a control model for the hybrid powertrain optimisation. The model is specified as a multi-domain physical model in MATLAB Simscape, which captures the key electrical, mechanical and thermal energy flows in the vehicles. By applying hand crafted boundary conditions, this model can be simulated either in the forwards or backwards direction, and it can easily be simplified as required to address specific control problems. Modelling in the forwards direction, the driver inputs are specified, and the vehicle response is the model output. In the backwards direction, the vehicle velocity as a function of time is the specified input, and the engine torque, and fuel consumption are the model outputs. The model represents a parallel hybrid vehicle, which is being developed in the TC48 project. The project goal is to produce a prototype of a plug-in parallel hybrid system which is integrated into existing front wheel drive powertrains with modest additional engineering, cost, volume, and mass requirements. This paper explains the motivation for the project, and presents examples of the simulations which were used to guide the design. The vehicle simulation models used to evaluate the layout options are described and discussed. Sensitivity analyses are presented which informed the design decisions. A novel use of the Simscape component of MATLAB/Simulink which allows the same model structure to be used for both forwards and backwards simulations is demonstrated. This method has the possibility for more general application, and a toolbox is being developed which assists the generation of mathematical models of this type

Design Optimization of Full-Wave EM Models by Low-Order Low-Dimension Polynomial Surrogate Functionals

A practical formulation for EM-based design optimization of high-frequency circuits using simple polynomial surrogate functionals is proposed in this paper. Our approach starts from a careful selection of design variables and is based on a closed-form formulation that yields global optimal values for the surrogate model weighting factors, avoiding a large set of expensive EM model data, and resulting in accurate low-order low-dimension polynomials interpolants that are used as vehicles for efficient design optimization. Our formulation is especially suitable for EM-based design problems with no equivalent circuital models available. The proposed technique is illustrated by the EM-based design optimization of a Ka-band substrate integrated waveguide (SIW) interconnect with conductor-backed coplanar waveguide (CBCPW) transitions, a low crosstalk PCB microstrip interconnect structure with guard traces, and a 10-40 GHz SIW interconnect with microstrip transitions on a standard FR4-based substrate. Three commercially available full-wave EM solvers are used in our examples: CST, Sonnet and COMSOL

EV-EcoSim: A grid-aware co-simulation platform for the design and optimization of electric vehicle charging infrastructure

To enable the electrification of transportation systems, it is important to understand how technologies such as grid storage, solar photovoltaic systems, and control strategies can aid the deployment of electric vehicle charging at scale. In this work, we present EV-EcoSim, a co-simulation platform that couples electric vehicle charging, battery systems, solar photovoltaic systems, grid transformers, control strategies, and power distribution systems, to perform cost quantification and analyze the impacts of electric vehicle charging on the grid. This python-based platform can run a receding horizon control scheme for real-time operation and a one-shot control scheme for planning problems, with multi-timescale dynamics for different systems to simulate realistic scenarios. We demonstrate the utility of EV-EcoSim through a case study focused on economic evaluation of battery size to reduce electricity costs while considering impacts of fast charging on the power distribution grid. We present qualitative and quantitative evaluations on the battery size in tabulated results. The tabulated results delineate the trade-offs between candidate battery sizing solutions, providing comprehensive insights for decision-making under uncertainty. Additionally, we demonstrate the implications of the battery controller model fidelity on the system costs and show that the fidelity of the battery controller can completely change decisions made when planning an electric vehicle charging site.Comment: This paper has been accepted for publication at the IEEE Transactions on Smart Gri

Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes

2019 Spring.Includes bibliographical references.With the continuous miniaturization in the latest VLSI technologies, manufacturing uncertainties at nanoscale processes and operations are unpredictable at the chip level, packaging level and at board levels of integrated systems. To overcome such issues, simulation solvers to model forward propagation of uncertainties or variations in random processes at the device level to the network response are required. Polynomial Chaos Expansion (PCE) of the random variables is the most common technique to model the unpredictability in the systems. Existing methods for uncertainty quantification have a major drawback that as the number of random variables in a system increases, its computational cost and time increases in a polynomial fashion. In order to alleviate the poor scalability of standard PC approaches, predictor-corrector polynomial chaos scheme and hyperbolic polynomial chaos expansion (HPCE) scheme are being proposed in this dissertation. In the predictor-corrector polynomial scheme, low-fidelity meta-model is generated using Equivalent Single Conductor (ESC) approximation model and then its accuracy is enhanced using low order multi-conductor circuit (MCC) model called a corrector model. In HPCE, sparser polynomial expansion is generated based on the hyperbolic criterion. These schemes result in an immense reduction in CPU cost and speed. This dissertation presents the novel approach to quantify the uncertainties in multi-walled carbon nano-tubes using these schemes. The accuracy and validation of these schemes are shown using various numerical examples

A Review of Bayesian Methods in Electronic Design Automation

The utilization of Bayesian methods has been widely acknowledged as a viable solution for tackling various challenges in electronic integrated circuit (IC) design under stochastic process variation, including circuit performance modeling, yield/failure rate estimation, and circuit optimization. As the post-Moore era brings about new technologies (such as silicon photonics and quantum circuits), many of the associated issues there are similar to those encountered in electronic IC design and can be addressed using Bayesian methods. Motivated by this observation, we present a comprehensive review of Bayesian methods in electronic design automation (EDA). By doing so, we hope to equip researchers and designers with the ability to apply Bayesian methods in solving stochastic problems in electronic circuits and beyond.Comment: 24 pages, a draft version. We welcome comments and feedback, which can be sent to [email protected]