Yingqi Gu

Smart procurement of naturally generated energy (SPONGE) for PHEVs

ABSTRACT In this paper, we propose a new engine management system for hybrid vehicles to enable energy providers and car manufacturers to provide new services. Energy forecasts are used to collaboratively orchestrate the behaviour of engine management systems of a fleet of plug-in hybrid electric vehicle (PHEVs) to absorb oncoming energy in a smart manner. Cooperative algorithms are suggested to manage the energy absorption in an optimal manner for a fleet of vehicles, and the mobility simulator SUMO (Simulation of Urban MObility) is used to demonstrate the efficacy of the proposed idea.

Optimal distributed consensus algorithm for fair V2G power dispatch in a microgrid

Among the many motivations to encourage the use of Electric Vehicles (EVs) there is the attractive possibility to implement Vehicle-to-Grid (V2G) functionalities. They are attractive both for EV owners, who can sell their own energy to the grid when they do not need to travel, and also for the power grid, as the stored energy can be used to back-up the fluctuating energy produced from renewable sources or to improve the grid stability at critical times. In this paper we illustrate a distributed algorithm that solves the V2G problem in a fair manner, trying to achieve an optimal trade-off between power generation costs and inconvenience to the vehicle owner. Results are shown and discussed for a case study simulated in the OpenDSS power system environment.

Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-In Hybrid Electric Buses

We discuss a recently introduced ECO-driving concept known as smart procurement of naturally generated energy (SPONGE) in the context of plug-in hybrid electric buses. Examples are given to illustrate the benefits of this approach to ECO-driving. Finally, distributed algorithms to realize SPONGE are discussed, paying attention to the privacy implications of the underlying optimization problems.

A Distributed and Privacy-Aware Speed Advisory System for Optimizing Conventional and Electric Vehicle Networks

One of the key ideas to make intelligent transportation systems work effectively is to deploy advanced communication and cooperative control technologies among vehicles and road infrastructures. In this spirit, we propose a consensus-based distributed speed advisory system that optimally determines a recommended common speed for a given area in order that the group emissions, or group battery consumptions, are minimized. Our algorithms achieve this in a privacy-aware manner; that is, individual vehicles do not reveal in-vehicle information to other vehicles or to infrastructure. A mobility simulator is used to illustrate the efficacy of the algorithm, and hardware-in-the-loop tests involving a real vehicle are given to illustrate user acceptability and ease of deployment.

Pedestrian-Aware Engine Management Strategies for Plug-In Hybrid Electric Vehicles

Electric vehicles (EVs) and plug-in hybrid EVs (PHEVs) are increasingly being seen as a means of mitigating the pressing concerns of traffic-related pollution. While hybrid vehicles are usually designed with the objective of minimizing fuel consumption, in this paper we propose a engine management strategies that also consider environmental effects of the vehicles to pedestrians outside of the vehicles. Specifically, we present the optimisation-based engine energy management strategies for PHEVs that attempt to minimize the environmental impact of pedestrians along the route of the vehicle, while taking account of route-dependent uncertainties. We implement the proposed approach in a real PHEV and evaluate the performance in a hardware-in-the-loop platform. A variety of simulation results are given to illustrate the efficacy of our proposed approach.

Optimised consensus for highway speed limits via intelligent speed advisory systems

In this paper, an application based on the Intelligent Speed Adaptation (ISA) system is proposed to reduce CO2 emissions of vehicles running on the highway. We apply the idea of optimised consensus to solve the emission optimisation problem in a simplified highway scenario through simulation study. Our approach shows that total CO2 emissions of vehicles can be minimised if all vehicles follow the reference speed signal derived from the ISA.

An intelligent speed advisory system for electric vehicles

Intelligent Transportation Systems (ITS) can be used to involve vehicles and the road infrastructure to cooperatively implement a number of innovative and useful applications. Here, we explore the possibility to adopt a consensus based distributed speed advisory system to determine the optimal recommended speed in urban areas where only electric vehicles are allowed to travel (e.g., in the city centre). The optimality criterion is to maximise the energy efficiency of a fleet of vehicles travelling in the restricted area, and we adopt recently proposed distributed privacy-preserving consensus algorithms to achieve the desired objective.

Cooperative control and smart procurement of naturally generated energy (SPONGE) for PHEVs

Electric vehicles can potentially be the best means of transportation for improving air quality, provided that they are powered by electricity from natural gas or wind, water or solar power. In this paper we describe a simple cooperative algorithm that exploits the energy management units of Plug-in Hybrid Electric Vehicles (PHEVs) to absorb the expected forthcoming energy available from renewable sources. The proposed approach bridges the gap between mobility patterns and power grid constraints, and allows to prevent green energy from being wasted while at the same time reducing the complexity burden of the power grid to charge unexpected loads of electric vehicles. Simulation results are given to show the efficacy of the proposed method.