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EB2020-STP-068

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Abstract

Mr. Steve Miller, MathWorks, GERMANY

Mr. Jan Janse van Rensburg, MathWorks, GERMANY


The engineering objective is to create a virtual design tool that can evaluate regenerative brake control algorithms in vehicles under various conditions. This includes but is not limited to variations in braking hardware, electronic components, energy storage technologies, driving conditions, and vehicle weight distribution. Conducting these tests on vehicles would be prohibitively expensive, potentially risky for those running the test, and is not repeatable. Exclusively testing these designs on hardware prototypes would also restrict the options that are considered to energy storage technologies that have already been built.


The model used enables the combination of physical systems (mechanical, electrical, thermal, fluid) and the control system within a single simulation environment. Using simulation, designs for integrating novel energy storage technologies are evaluated to identify those that are likely to meet system requirements. A model of the vehicle, including a multibody suspension, brake hardware, and the powertrain is used to assess system requirements. The virtual vehicle model is developed using MATLAB, Simulink, and Simscape. Abstract models are used to refine the requirements for the energy storage system including incorporating limits for the various technologies, such as charge and discharge rates from the battery. The control algorithms necessary for power management are integrated with the physical system, and performance characteristics are calculated dynamically during simulation.


Using this modeling and simulation framework, we were able to develop and evaluate different architectures for regenerative braking systems. Power management algorithms were developed and tuned to optimize performance characteristics such as range while meeting vehicle dynamics requirements. Tests under conditions that are challenging to reproduce were conducted on a range of vehicle types and weight distributions to identify edge cases for the regenerative braking system.

EuroBrake 2021

BCN

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Steve Miller is a product manager at MathWorks for simulation tools that are used to design mechanical, electrical, and hydraulic systems. He studied mechanical engineering at Cornell University and Stanford University with a focus on control systems and mechatronics. He spent 5 years developing control algorithms for anti-lock braking systems at the General Motors Proving Grounds, which included test-driving those algorithms in prototype vehicles. He then performed onsite consulting for simulation of vehicle dynamics at BMW and Audi in Germany. At MathWorks, Steve works directly with engineers in the automotive, aerospace, and industrial machinery industries.

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