2x parameterised DFN cell models (NMC & LFP). In support the new open standard Battery Parameter eXchange (BPX), an outcome of the Faraday Institution Multi-scale Modelling project.

Efficient solver for P2D model of Li-ion batteries based on OpenFOAM

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's …

Library for detecting anomalies in signals

SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.

Houses code for an anomaly detection pipeline that can detect anomalies in time series data in real-time using TadGAN, Spark and Kafka

TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network

This project implements a Generative Adversarial Network (GAN) to detect fraudulent transactions from credit card data. The model architecture includes separate generator and discriminator networks…

GAN based model for time series anomaly detection.

Multivariate Anomaly Detection with GAN (MAD-GAN) PyTorch modern implementation.

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks Alexander Geiger, Dongyu Liu, Sarah Alnegheimish, Alfredo Cuesta-Infante, Kalyan Veeramachaneni

Official PyTorch implementation for the paper ADA-GAD: Anomaly-Denoised Autoencoders for Graph Anomaly Detection (AAAI 2024).

This is a Pytorch implement of our MEGA: Multiscale Wavelet Graph AutoEncoder for Multivariate Time-Series Anomaly Detection

Implementation of Zero-Shot Learning algorithm using Word2Vecs as class embeddings

Battery charging schedule optimization to minimize lithium-ion battery degradation.

Fast and flexible physics-based battery models in Python

Implement model predictive control on a physics-based battery model for minimizing charging time while maximizing lifetime.

A Matlab framework based on a finite volume model suitable for Li-ion battery design, simulation, and control

Lyapunov based based backstepping controller was developed to control an induction motor.

Solver for pseudo-2D model of Li-ion battery based on Finite difference Method. Incorporation of JAX for the nonlinear solver.

Interactive Gaussian process sensitivity analysis of a P2D-SEI battery degradation model

Numerical Implementation (Finite Difference) of the Pseudo-two-Dimensional Model for Lithium-ion Batteries

The dataset is generated by P2D model for Li-ion battery, the out put will be the degradation of battery during charging.

simulation of Lithium ion batteries using Pseudo two-dimensional (P2D) model

Pseudo-2D Newman-type model of a Li ion battery

A pytorch implementation of the methods described in the paper "Deep Reinforcement Learning for Continuous Electric Vehicles Charging Control With Dynamic User Behaviors"

Chargym simulates the operation of an electric vehicle charging station (EVCS) considering random EV arrivals and departures within a day. This is a generalised environment for charging/discharging…

This code was written within the dissertation of Ola Pronobis "Charge management concepts with integrated requirements management in case of unpredictable behavior of electric vehicle fleets" at TU…