Job Description

A leading premium automotive business and leading to move towards electric autonomous vehicles.

WHAT TO EXPECT

Are you an experienced Vehicle Thermal Management Control Algorithm Development Engineer who is interested in playing a critical role in the development and optimisation of control algorithms focused on improving vehicle efficiency, specifically in the thermal domain?

We have an opportunity to deliver on just that collaborating in partnership with cross-functional teams to contribute to the advancement of our automotive systems. This is also a chance to create an ecosystem that encourages innovative ideas for vehicle efficiency.

Key Accountabilities and Responsibilities

• Develop and refine model-based thermal control algorithms to optimize the performance and efficiency of automotive systems
• Carry out research, analyse data, and propose innovative solutions to address thermal & electrical challenges within the vehicle
• Collaborate with the control systems team, powertrain engineers, and other stakeholders to integrate energy control algorithms seamlessly into the overall vehicle systems.
• Build energy focused systems controls by means of advanced control techniques.
• Create an ecosystem and encourage innovative ideas for vehicle efficiency.

• You\'ll be educated to degree standard in either Mechanical Engineering, Thermal engineering, Control Systems engineering or a related field (or have the equivalent level experience)
• You\'ll hold expertise in thermal systems, heat transfer, thermodynamics or a related discipline
• You\'ll also come to the role with data modelling, reduced order modelling, Model based controller expertise.
• Experience in model-based development tools, such as MATLAB/ Simulink, GT-Suite or similar platforms to develop and implement control algorithms, preferably in the automotive industry.
• And finally, you\'ll have experience with vehicle thermal management systems, HVAC systems, Low voltage energy management or related subsystems is highly desirable and have worked in creating control systems using ANN, Fuzzy Logic or Neuro-Fuzzy.

JLR