Chiao Ting Li

Synergistic control of plug-in vehicle charging and wind power scheduling

Significant synergy exists between plug-in electric vehicles (PEVs) and wind energy: PEVs can be the demand response to mitigate the intermittent wind power outputs, and wind energy can provide low-carbon electricity to PEVs. This paper presents a hierarchical control algorithm to realize this synergy by integrating the PEV charging and wind power scheduling. The control algorithm consists of three levels: the top-level controller optimizes the scheduling for the conventional power plants and wind power; the middle-level controller plans PEV charging to achieve load following based on the battery state of charge and plug-off time of each vehicle; the bottom-level controller uses grid electricity frequency as the feedback cue to control PEV charging and serves as the ancillary service to the grid. Numerical simulations show that the integrated controller can improve the grid frequency regulation and overall electricity generation cost without sacrificing the PEVs charging completion.

Decentralized charging algorithm for electrified vehicles connected to smart grid

Intelligent management of power generation and dispatching is important when renewable energy sources and electrified vehicles (EV/PHEV) are introduced to the grid. Intermittency of renewable power and vehicle charging loads disturbs power supply and demand and could cause instability. Fortunately, EV/PHEV can be connected as controllable load or even used as energy storage, which makes it possible to reduce their negative impact and can even be explored to improve grid resilience. By coordinating power generation and charging, it is possible to reduce power generation cost and carbon emission. To improve practicality, a decentralized charging algorithm is formulated by emulating the charging pattern identified through linear programming (LP) optimization solutions. The resulting decentralized control algorithm is a function of forecasted total power demand on the grid, estimated number of vehicles, estimated EV/PHEV plug off time, and state of charge of the vehicle battery. Simulation results are presented to demonstrate the performance of the proposed decentralized algorithm.

Integration of plug-in electric vehicle charging and wind energy scheduling on electricity grid

Plug-in electric vehicles (PEVs) and wind energy are both key new energy technologies. However, they also bring challenges to the operation of the electricity grid. Charging a large number of PEVs requires a lot of grid energy, and scheduling wind energy is not trivial because of the intermittency. In this paper we propose a hierarchical control algorithm which integrates PEV charging and wind energy scheduling. It explores the controllable nature of PEV charging to accommodate the intermittent wind energy. The algorithm consists of three levels: the top-level controller solves the hourly scheduling of wind energy (and conventional generation) through an optimization problem, the middle-level controller determines sub-hourly scheduling of PEV charging to achieve load following, and the bottom-level controller uses grid frequency deviation as the feedback cue to control PEV charging in real time. The integrated controller achieves multiple goals, including optimal electricity cost, replacing fossil fuel generation by wind energy, reducing ancillary service by controlled PHV charging, and improving the quality of electricity service.

Optimal configuration design for hydraulic split hybrid vehicles

Hydraulic hybrid vehicles are more suitable for heavy-duty applications in urban driving than hybrid electric vehicles because of the high power density and low cost of hydraulic devices. However, the low rotational speeds of hydraulic pump/motor and the low energy density of the accumulator impose severe constraints on the design and control for these vehicles. The split configuration is an efficient and more flexible transmission configuration and is the focus of this study. A three-step design methodology is developed to systematically and exhaustively explore all possible split configurations using two planetary gears: Step 1 checks mechanical feasibility of configurations; Step 2 develops optimal power management inspired by Pontryagins Minimum Principle; and Step 3 finds optimal component sizes. After the screening, we identify three new configurations that achieve best fuel economy for the hydraulic vehicle/drive cycle studied, together with their best design and control executions.

Decentralized Charging of Plug-In Electric Vehicles

Plug-in electric vehicles (PEVs) are equipped with sizable batteries to replace fossil fuel with electric energy. The electric grid may be stressed when a large number of PEVs charge their batteries, especially during peak hours. This paper presents a PEV charging control algorithm, which achieves balance between the system-level objective (valley filling) and individual-level objective (full battery charging). In addition, grid frequency regulation is achieved through a two-level control algorithm, which ensures robustness and reduces reliance on conventional ancillary services. This two-level control algorithm is scalable because it is designed for decentralized implementation. In other words, the algorithm works with indefinite numbers of PEVs as long as the load is within the grid capacity.Copyright

Design of Power-Split Hybrid Vehicles With a Single Planetary Gear

This paper presents a systematic design methodology for split hybrid vehicles using a single planetary gearset (PG) as the transmission. The design methodology consists of four steps: 1) analyze clutch locations on the PG and operation modes, 2) generate dynamic models, 3) evaluate drivability (acceleration performance) via forward simulations, and 4) optimize the fuel economy using the dynamic programming technique. The 1-PG split hybrid transmission can have 12 configurations, and each configuration can have four operation modes when three clutches are added. This methodology systematically evaluates all configuration candidates and identifies the optimal design, and we demonstrate how it helps to identify a simplified design based in the output-split configuration used by the Chevy Volt. The simplified design, named the Volt−, has only two of the four operation modes of the original Volt. The Volt− achieves the same fuel economy as the original Volt in the FUDS cycle, and has only slightly reduced drivability and fuel economy in the HWFET cycle. In addition, an improved design based on the input-split configuration used by the Toyota Prius is also identified, named the Prius+, which has one additional mode than the original Prius. The Prius+ outperforms the Prius in both drivability and fuel economy.Copyright