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Found 4 papers, 1 papers with code
Eco-PiNN: A Physics-informed Neural Network for Eco-toll Estimation
The eco-toll estimation problem quantifies the expected environmental cost (e. g., energy consumption, exhaust emissions) for a vehicle to travel along a path.
Vehicle Emissions Prediction with Physics-Aware AI Models: Preliminary Results
Given an on-board diagnostics (OBD) dataset and a physics-based emissions prediction model, this paper aims to develop an accurate and computational-efficient AI (Artificial Intelligence) method that predicts vehicle emissions.
A Physics Model-Guided Online Bayesian Framework for Energy Management of Extended Range Electric Delivery Vehicles
A physics model-guided online Bayesian framework is described and validated on large number of in-use driving samples of EREVs used for last-mile package delivery.
Adversarial Attacks on Reinforcement Learning based Energy Management Systems of Extended Range Electric Delivery Vehicles
Adversarial examples are firstly investigated in the area of computer vision: by adding some carefully designed ''noise'' to the original input image, the perturbed image that cannot be distinguished from the original one by human, can fool a well-trained classifier easily.
