Abstract
This paper proposes a hybrid model predictive control (MPC) controller for yaw stability control of distributed drive electric vehicles based on the nonlinear dynamic model. To reduce the computational burden during the optimization process of MPC problem, the vehicle model is formulated by approximating the magic tire model with a set of piecewise linear functions. The dynamic model is equivalently translated into a mixed logical dynamical (MLD) system which is used to design the hybrid MPC controller. To improve the energy efficiency of the system while tracking the reference signals, the input signals are restricted in the high efficiency range of in-wheel motors. Finally, simulation results of different inputs and the comparison of closed-loop and open-loop system indicate the suggested hybrid MPC control method is able to fleetly track the reference and stabilize the vehicle effectively for the test maneuvers.
| Original language | English |
|---|---|
| Pages (from-to) | 2518-2523 |
| Number of pages | 6 |
| Journal | Energy Procedia |
| Volume | 158 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 10th International Conference on Applied Energy, ICAE 2018 - Hong Kong, China Duration: 22 Aug 2018 → 25 Aug 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Distributed drive electric vehicles
- Mixed logical dynamical (MLD) model
- Model predictive control (MPC)
- Yaw stability control
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