Learnings

Outcomes

• A model of the dynamic charging system based on the inductive power transfer technology is provided in Matlab/Simulink, which can be used for the demand analysis.
• The renewable energy source and storage system were modelled using Matlab for reducing the grid demand of the dynamic charging system
• A small-signal impedance model of the dynamic charging system is provided for the interaction analysis between the dynamic wireless charging system and the grid.
• The topologies of the power station for the dynamic wireless charging are provided in case of protection and maintenance.
•  A laboratory test rig was set up to explore wireless and wired charging together with battery banks. This can be used for future projects.
• An EV choice model is proposed to estimate the DWC charging demand. In this model, EV choices among different charging service providers are quantified based on the customer satisfaction. The renewable energy support is estimated using the Markov chain algorithm.
• The grid impact of DWC charging demand is assessed using power flow analysis in a multi-bus AC grid. Moreover, the guidance of DWC electricity procurement is proposed based on the grid impact analysis.
• A multi-objective optimization for DWC system is proposed to analyse its economic viability, which brings a trade-off optimization between the profit of the DWC system and the grid impact in each horizon.

Lessons Learnt

The technical details of the dynamic wireless charging system are explained including the theory of wireless power transfer, and the topology and function of each of the components in the transmitter and receiver. The dynamic wireless charging technology for EVs is feasible in technical theory. The different types of the transmitter track are summarized. The multi-unit track is built with a series of coils whose dimension is similar or smaller to the receiver coils. It has advantages of high efficiency and low EMF radiation. However, this track leads to high cost and complex control because it needs to frequent switch to turn on a portion of track which is under the moving EV. The other track is extended track whose dimension is much longer than receiver coil. The ferrite core can be used for the extended track to achieve a thin footprint which achieves a large misalignment and also reduce the cost.

A test rig design is presented to create a small-scale testing environment that could accurately simulate the full-scale implementation of dynamic wireless charging system. The model of the dynamic wireless charging is built. The demand analysis based on the model is carried out. In the way to evaluate the demand of dynamic wireless charging system, Motorway 25 are picked for car flow analysis. If the charging rate is 30 kW and only 1 lane (30 km) for charging, the power required from the grid is 0.33 GW at peak car flow. For an hour charging at 3.3 GW, the energy required from the grid is equivalent to 78 domestic annual consumption. For 4 lanes, it is equivalent to 310 domestic annual consumption. The results show that the demand from the dynamic wireless charging system is large and should be carefully considered by the grid.

Two topologies of the power substation for the dynamic wireless charging system are proposed, shown in the supporting document as Figure 1, which are the unit-based power station and the D.C. based power station. Both topologies have their own protection, maintenance and ability to integration other resources such as solar power and storage system.

The interaction between the dynamic wireless charging system and the A.C. grid is carried out via the stability analysis of the grid-connected inverter, which is used to transport the power from the A.C. grid to the dynamic wireless charging system. It is found that a weak grid may result in the instability of dynamic wireless charging system.

The comparative studies between conductive charging and dynamic wireless charging was analysed. The charging ratings from home charging level of 3.7 kW to ultra-rapid charging level of 150 kW are included for conductive charging. The customer satisfaction model and choose model are built to simulate the driver’s choice for different charging technologies and different charging ratings. It is found that even the dynamic wireless charging does not possess highest charging rating, it is still an attractive choice for drivers because the dynamic wireless charging can achieve the charging while vehicles are in motion. This will potentially reduce the size of the battery.

A comprehensive model to evaluate the economic viability for the DWC system including a DWC lane, renewable integration and storage system has been validated. It is shown via the proposed choice model that the drivers prefer the quick charging speed if the charging price is below 0.56 £/kWh. Therefore, the DWC is more attractive over the conductive charging because of its capability of non-stop charging. It has been validated via the developed DWC model that the proposed multi-objective optimization policy can track the Pareto frontier of the DWC profit and the grid impact accurately. Moreover, using solar generation at the substation helps to produce the higher profit of the DWC system. For example, compared to January, daily profit in May is 180% higher.

In figure 2 in the supporting document, with the multi-objective optimization policy investigated, the payback period is 8.9 years, while fixed charging price strategy is 12.5 years. Using this policy, the tight grid impact limit will not have a significant impact, which only postpones 8.9-year payback period to 9.3 years. While the DWC system with fixed charging price strategy postpone 12.5-year payback period to 15 years. If the efficiency increases to 90% and the cost of the DWC lane reduces to 50%, the payback period will be shortened to 87% and 74%.

Dissemination

The project outcomes have been disseminated at the events below:

• The IEEE event of Decarbonisation of Transport through Electrification Summit on the 20th March 2019, Best Poster Presentation awarded
• Transport Futures Conference on the 6th June 2019, Best Poster Prize awarded
• Sustainable Transport Workshop – Landscape, Opportunities and Capabilities on 9th July 2019
• Intelligent transportation young researcher conference on 11th October 2019

The publication based on the outcomes of the project are listed below:

• IEEE transactions on Transportation Electrification, "Economic viability of the dynamic wireless charging system", submitted on 8th Oct. 2020. Revise & Resubmit 2021 .
• William Seward, Ryan Huxtable, Bradley Beynon, Arnas Zvirblys, Nicolas Camacho-Hunt, Maurizio Albano, Liana Cipcigan, “Modelling of Static Wireless Electric Vehicle Charging and its Impact on a Typical GB Distribution Network”, 54th International Universities Power Engineering Conference, UPEC 2019, Bucharest, Romania, 3-6 September, 2019
• Dominic Dattero Snell; Aaron Parkes; Thomas Edwards; Liana Cipcigan, “Small Scale Multivariate Testing of Dynamic Wireless Charging”, 55th International Universities Power Engineering Conference (UPEC), September 2020