Advanced Automotive Propulsion Systems

Lead Research Organisation: University of Bath
Department Name: Mechanical Engineering

Abstract

The recent drive to decarbonise transport has prompted a sharp rise in the global sales of electric vehicles (EVs). Charging infrastructure provides an interface between the transport and energy sectors and enables the integration of EVs into the electrical network. The transition to EVs requires huge investments into new public and private charging infrastructure to meet the mobility demands of the population. To maximise their utilisation, new charging infrastructure will need to be installed in areas of high existing and future demand. Furthermore, as the adoption of EVs continues to grow, at peak times the energy demand due to charging could surpass the capacity of local transformers, thus requiring expensive grid upgrades. As we move towards a more distributed energy system, emerging players, such as EVs, are beginning to form vast networks with complex interactions. Modelling the interactions between EVs and the grid is made challenging by the following factors. Firstly, there is a large amount of technological diversity within the range of available EVs and chargers, making it difficult to accurately represent the whole system. Secondly, the introduction of smart charging functionalities, where the charging time and power is shifted based on grid requirements and the vehicle owner's needs, introduces more potential flexibility and degree of control over charging. Thirdly, the battery charging dynamics dictating the charging demand varies between EV models and is sensitive to the battery state-of-charge. Finally, the movement and charging patterns of EVs are dictated by human behaviour, which is often difficult to predict and rationalise. This complexity means that models used to capture the aggregated dynamics of the system tend to rely upon simplified representations that often deviate substantially from reality. Over-simplification of these dynamic interactions can potentially have significant consequences. For example, it could lead to a mismatch of energy supply and demand, uneconomic grid development, and ultimately delayed and/or high cost in system decarbonisation. Current attempts to model and optimise EV charging tend to make unrealistic assumptions about consumer travel and charging behaviour. Moreover, there has been limited spatiotemporal modelling of EV-grid interactions that accurately captures the grid topology at different scales. In addition, attempts at long-term demand forecasting often do not accommodate for changes in EV and charging technology, as well as user behaviour. This PhD aims to answer the following research questions: 1) What will future EV charging demand look like, and how will it respond to evolving technology and user behaviour? 2) What is the current and future impact of EV charging on the grid, and where might reinforcement be required? 3) Where should new chargers be installed to meet people's mobility needs and reduce the need for grid reinforcement? The goal of this research is to develop a high-fidelity spatiotemporal model to build a better understanding of the current and future aggregated group dynamics of EV charging demand. This will be achieved using a combination of data-driven and agent-based modelling techniques. The key parameters that influence this aggregated demand should be identified to inform the spatiotemporal modelling, optimisation, and interactions between the charging and grid infrastructure. The research should inform the future infrastructure rollout strategy of network operators and local councils. The aim is that this research will enable cheaper and faster integration of EVs into the grid and thus accelerate the decarbonisation of the automotive and power sectors.

Planned Impact

Impact Summary

This proposal has been developed from the ground up to guarantee the highest level of impact. The two principal routes towards impact are via the graduates that we train and by the embedding of the research that is undertaken into commercial activity. The impact will have a significant commercial value through addressing skills requirements and providing technical solutions for the automotive industry - a key sector for the UK economy.

The graduates that emerge from our CDT (at least 84 people) will be transformative in two distinct ways. The first is a technical route and the second is cultural.

In a technical role, their deep subject matter expertise across all of the key topics needed as the industry transitions to a more sustainable future. This expertise is made much more accessible and applicable by their broad understanding of the engineering and commercial context in which they work. They will have all of the right competencies to ensure that they can achieve a very significant contribution to technologies and processes within the sector from the start of their careers, an impact that will grow over time. Importantly, this CDT is producing graduates in a highly skilled sector of the economy, leading to jobs that are £50,000 more productive per employee than average (i.e. more GVA). These graduates are in demand, as there are a lack of highly skilled engineers to undertake specialist automotive propulsion research and fill the estimated 5,000 job vacancies in the UK due to these skills shortages. Ultimately, the CDT will create a highly specialised and productive talent pipeline for the UK economy.

The route to impact through cultural change is perhaps of even more significance in the long term. Our cohort will be highly diverse, an outcome driven by our wide catchment in terms of academic background, giving them a 'diversity edge'. The cultural change that is enabled by this powerful cohort will have a profound impact, facilitating a move away from 'business as usual'.

The research outputs of the CDT will have impact in two important fields - the products produced and processes used within the indsutry. The academic team leading and operating this CDT have a long track record of generating impact through the application of their research outputs to industrially relevant problems. This understanding is embodied in the design of our CDT and has already begun in the definition of the training programmes and research themes that will meet the future needs of our industry and international partners. Exchange of people is the surest way to achieve lasting and deep exchange of expertise and ideas. The students will undertake placements at the collaborating companies and will lead to employment of the graduates in partner companies.

The CDT is an integral part of the IAAPS initiative. The IAAPS Business Case highlights the need to develop and train suitably skilled and qualified engineers in order to achieve, over the first five years of IAAPS' operations, an additional £70 million research and innovation expenditure, creating an additional turnover of £800 million for the automotive sector, £221 million in GVA and 1,900 new highly productive jobs.

The CDT is designed to deliver transformational impact for our industrial partners and the automotive sector in general. The impact is wider than this, since the products and services that our partners produce have a fundamental part to play in the way we organise our lives in a modern society. The impact on the developing world is even more profound. The rush to mobility across the developing world, the increasing spending power of a growing global middle class, the move to more urban living and the increasingly urgent threat of climate change combine to make the impact of the work we do directly relevant to more people than ever before. This CDT can help change the world by effecting the change that needs to happen in our industry.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S023364/1 01/04/2019 30/09/2027
2432323 Studentship EP/S023364/1 01/10/2020 30/09/2024 Isaac FLOWER