APAS – Automated Powerunit Architecture Selection and Control Strategy Generation
This IDE funded project aims to develop capability to model and simulate powerunit systems and controllers for a variety of architectures. These models are then used to assess attribute performance, which in turn then optimises the vehicle architecture to meet a set of targets and requirements.
McLaren Automotive (Lead)
University of Bath
Ricardo UK Ltd
total project spend
Two PhD students from the University of Bath will work in close connection with McLaren Automotive and Ricardo to:
Develop software that allows multiple attributes to be assessed for a single vehicle model, and the architecture to be modified based on these results.
Develop enabling technologies and advanced control and optimisation approaches to allow for the optimum definition of a vehicle powertrain architecture.
The APAS project unlocked the opportunity to perform optimisation of a powertrain architecture based on multiple requirements like lap time, CO2 and acceleration performance.
The project focussed on a single architecture to develop the optimisation routines and developed methods to assess the effectiveness of different optimisation approaches.
A method was developed to automatically calibrate the torque split hybrid strategy for a given architecture. This was used in the optimisation routine to give a true like-for-like comparison.
The APAS project has:
Established a methodology for characterising powertrain components in a way that is useful to an optimiser
Defined a general optimisation process for powertrain component selection using Genetic Algorithms
Developed a tool for comparing Equivalent Consumption Minimization Strategy with Dynamic Programming methods for fuel economy optimisation
Delivered a software that McLaren can integrate in their pipeline to evaluate different alternatives in the future
An IDE Funded Project