Battery Modelling and Controls Engineer

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Summary

 

We are looking for an experienced battery modelling and controls engineer to contribute to developing advanced battery models, state estimation and control algorithms to be deployed on Brill Power’s cutting-edge battery management technology. You will join a small and dynamic team in a permanent, full time role and report directly to our Chief Data Scientist.

 

Overview

As a battery modelling and controls engineer at Brill Power, you will contribute to defining and delivering the next generation of battery state estimation, diagnostics and prognostics algorithms for both stationary energy storage and electric vehicles. You will work closely with our Chief Data Scientist and the rest of the team to bring to market novel algorithms that leverage Brill Power’s advanced battery control technology to go beyond the status quo in the industry.

If you are keen to develop new technologies and work in a dynamic field, this may be the role for you. You should be confident working autonomously while also being comfortable working with the team in a fast-paced environment. If you fill the majority of the qualifications listed below and are excited to work on cutting-edge battery technology, we want to talk to you.

Responsibilities

Main responsibilities will include:

  • Developing novel models and algorithms for battery state estimation (SoC, SoH…) and battery diagnostics and prognostics (fault detection, lifetime prediction…)

  • Implement prototype code to assess the performance of these algorithms

  • Stay up-to-date with the state-of-the-art in battery modelling and control by keeping on top of academic literature and attending relevant conferences

  • Analyse lab test data and customer field data to identify opportunities for software algorithm improvements

  • Designing and scheduling test plans for  parametrising and validating battery models, and  state estimation and prediction algorithms

  • Closely collaborating with the software and firmware teams to integrate new algorithms into our products’ production code

  • Be proactively involved in relevant collaborative project work with industrial and academic partners

Skills and Qualifications

  • PhD in engineering, mathematics, statistics, physics or equivalent fields, or a combination of education and work experience, with relevant research experience

  • Theoretical and practical knowledge of control theory, model-based control, recursive filtering techniques

  • Strong mathematical background in linear algebra, calculus, statistics

  • Well-versed in the theory and practical use of various optimization algorithms

  • Hands-on experience with deriving and solving ODE/PDE models

  • Proficient at programming for numerical computation in Python and/or Matlab

  • Experience with mathematical modelling of lithium-ion batteries

  • Experience developing and implementing state/parameter estimation algorithms

  • Applied machine learning or Bayesian inference experience is a plus

Benefits

 

In addition to a fun and friendly working environment, we offer:

  • Competitive salary, based on experience

  • 25 days of holiday plus bank holidays

  • Benefits package, including life insurance and medical cover

  • Full time, permanent role, with flexible working hours

  • In-office tea, coffee, & snacks

  • Regular team social events

 

Get in touch

Brill Power is an equal opportunity employer and welcome applications from all, without regard to their race, sex, disability, religion/belief, gender reassignment, national origin, sexual orientation or age.

Please send a CV and cover letter to hello@brillpower.com before 17 April 2020 clearly indicating where your past experience matches what we are looking for in this role.

© 2016-20 by Brill Power Ltd.

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