Open AccessLongitudinal Dynamic Modeling and Driving Cycle Tracking Control of an Electric-Driven Vehicle by Means of MATLAB/Simulink/Simscape
Author(s) -
András Szántó,
Sándor Hajdú,
Krisztián Deák
Publication year - 2022
Publication title -
periodica polytechnica. transportation engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 15
eISSN - 1587-3811
pISSN - 0303-7800
DOI - 10.3311/pptr.16197
Subject(s) - matlab , robustness (evolution) , driving cycle , control engineering , mechatronics , pid controller , control theory (sociology) , computer science , powertrain , traction control system , electric vehicle , control system , engineering , system dynamics , automotive engineering , control (management) , torque , temperature control , artificial intelligence , biochemistry , chemistry , power (physics) , physics , thermodynamics , electrical engineering , quantum mechanics , gene , operating system
MATLAB, Simulink, and Simscape are market-leading products in Model-Based Design (MBD). Applying acausal and causal modeling methods to model the physical plant and control algorithms of mechatronic systems results in high-fidelity virtual prototype models that can be used for Model-in-Loop (MiL) development. In this paper, an electric-driven vehicle is modeled, which can execute various driving cycle inputs. PID controllers are used in order to get the appropriate plant inputs. Idealized anti-lock braking system (ABS) and traction control system (TCS) algorithms provide robustness when the driving cycle input is near-infeasible. The control algorithm is validated in the cases of feasible and infeasible driving cycle inputs.