A Feedback and Feedforward Control Algorithm for a Manual Transmission Vehicle Simulation Model

Paper #:
  • 2018-01-1356

  • 2018-04-03
Recent advances in Automotive Electrical and Electronic Systems have also given pace to new methods of systems engineering, which includes the modelling and simulation of the physical systems. System modelling and simulation helps system designers to have an advanced assessment of system performance and its benefits, and in addition, in optimizing the design for efficiency and cost. One of the widely used approach for modelling a system is the deployment of physical system modelling tools, which makes the system modelling a lot easier and models thus developed demonstrate the results very close to actual system performance. Authors were challenged with a task of developing a full vehicle model, with a target to simulate the electrical system performance and perform digital tests like Battery Charge Balance, in addition to the fuel efficiency estimation. A vehicle is a complicated problem to model, due to the complexities of internal systems. Even more difficult task is to have a control algorithm which controls the vehicle model with the required control signals to follow the test specification. Particularly, simulating the control of a vehicle with a manual transmission is even more complicated due to the multiple associated control signals (Throttle, Brake, and Clutch) and interruptions like gear changes. In this paper, the development of a full vehicle model aimed at the assessment of electrical system performance of the vehicle during the development is discussed in brief, before the detailed discussion on the control algorithm which simulates the "drive behavior" for controlling the vehicle model to follow the desired velocity profile as per the selected Drive Cycle. A complete model of a vehicle with manual transmission was developed with all the required subsystems. A feedback and feedforward control algorithm was developed to control the vehicle model. The model was validated by performing a charge balance test on the vehicle's charging system, and model predictions were observed to be close to actual test results.
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