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MORFAE
Modeling, optimization and control of networked vehicles and vehicle fleets with heterogeneous drive technologies in real time
Funding program: BMBF, Mathematics for Innovation
Duration: 11/2022 to 10/2025
Project partners: University of Heidelberg, Robert Bosch GmbH
Sub-project of the Continuous Optimization WG: Multi-level iterations with sequential homotopy methods
The joint project MORFAE with the company BOSCH aims to realize the potential of mathematical MSO to promote "sustainable mobility in urban and rural areas". The aim is to develop real-time methods for calculating optimal driving modes for partially or fully autonomous, networked individual vehicles and interconnected entire vehicle fleets in road traffic. The aim is to minimize the total energy consumption of all vehicles while guaranteeing safety and conserving resources. Resource-limited vehicle computers and more powerful external infrastructure ("cloud"), which communicate with each other and with other vehicles, are available as computing capacities. One focus is on optimal operating strategies for vehicles that minimize CO2 emissions and energy consumption under uncertainties and strict constraints. Complex models for electric drives, combustion engines, hybrid drives with batteries and even combinations with fuel cells are to be used, which feature integer decisions and implicit discontinuities in the dynamics. Another focus is the much more complex - simultaneous - optimization of entire vehicle fleets with heterogeneous drive technology in a spatial segment. This leads to large distributed but specially structured optimization problems.
Building on preliminary work on novel sequential homotopy methods, the Clausthal University of Technology sub-project is developing new structure-exploiting numerical methods and investigating their suitability for the distributed solution of the underlying optimization problems in real time, particularly with regard to resource-limited onboard hardware systems