An Electronic Line-Shafting Control Strategy Based on Sliding Mode Observer for Distributed Driving Electric Vehicles

Huang, Hao; Tu, Qunzhang; Jiang, Cheng-Ming; Pan, Ming; Zhu, Changlin

doi:10.1109/access.2021.3062829

Cited by 10 publications

(3 citation statements)

References 42 publications

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“…The choice of machine to be installed in an electric vehicle depends on several parameters. Each range of machines has advantages and disadvantages related to production costs or procurement, as well as the desired application and defined specifications [10,11]. However, our research focuses on the utilization of a new type of machine in the automotive sector.…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of an Electric Vehicle Driven by a New Powertrain Technology Based on a Dual-Star Induction Machine

Benbouya,

Cheghib,

Chrenko

et al. 2024

WEVJ

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This article examines a new powertrain system for electric vehicles based on the dual-star induction machine, presented as a promising option due to its significant advantages in terms of performance, energy efficiency, and reliability. This system could play a key role in the evolution of electro-mobility technology. The dual-star induction machine reduces electromagnetic torque fluctuations, limits current harmonics, improves power factor, and enables half-speed operation. Our study focuses on the control strategy and operation of the traction chain for electric vehicles propelled by the dual-star induction machine (DSIM) using Matlab software with version 2017. We integrate the battery as the main energy source, along with three-level static converters for energy conversion in the vehicle’s four operating quadrants. We have opted for sliding mode control, which has proven to be feasible and robust against external disturbances. Although we have modeled driver behavior, we consider it as an aspect of control, to which we add the driving profile to guide our evaluation of the control to be used for vehicle operation. The results of our study demonstrate the reliability and robustness of DSIM for electric vehicle motorization and speed control. Promoting this technology is essential to improve the overall performance and efficiency of electric vehicles, especially in traction and braking modes for energy recovery. This underscores the importance of DSIM in the sustainable development of the electric transportation system.

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Section: Introductionmentioning

confidence: 99%

Sliding Mode Control of an Electric Vehicle Driven by a New Powertrain Technology Based on a Dual-Star Induction Machine

Benbouya,

Cheghib,

Chrenko

et al. 2024

WEVJ

View full text Add to dashboard Cite

show abstract

“…The existing motion control systems for DDEVs typically consist of a vehicle handling controller and four motor controllers [ 6 , 7 ]. The vehicle handling controller’s main objective is to accurately track movement references in different directions for DDEVs.…”

Section: Introductionmentioning

confidence: 99%

Parameter Optimization of Model Predictive Direct Motion Control for Distributed Drive Electric Vehicles Considering Efficiency and the Driving Feeling

Gao

Chai

2023

Sensors

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This paper presents a novel motion control strategy based on model predictive control (MPC) for distributed drive electric vehicles (DDEVs), aiming to simultaneously control the longitudinal and lateral motion while considering efficiency and the driving feeling. Initially, we analyze the vehicle’s dynamic model, considering the vehicle body and in-wheel motors, to establish the foundation for model predictive control. Subsequently, we propose a model predictive direct motion control (MPDMC) approach that utilizes a single CPU to directly follow the driver’s commands by generating voltage references with a minimum cost function. The cost function of MPDMC is constructed, incorporating factors such as the longitudinal velocity, yaw rate, lateral displacement, and efficiency. We extensively analyze the weighting parameters of the cost function and introduce an optimization algorithm based on particle swarm optimization (PSO). This algorithm takes into account the aforementioned factors as well as the driving feeling, which is evaluated using a trained long short-term memory (LSTM) neural network. The LSTM network labels the response under different weighting parameters in various working conditions, i.e., “Nor”, “Eco”, and “Spt”. Finally, we evaluate the performance of the optimized MPDMC through simulations conducted using MATLAB and CarSim software. Four typical scenarios are considered, and the results demonstrate that the optimized MPDMC outperforms the baseline methods, achieving the best performance.

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“…v xre f or wind disturbance. The authors in [36] propose the use of a permanent magnet synchronous motor as a powertrain to control longitudinal traction and generate yaw torque by varying the slips on the rear wheels, but they did not estimate the rear torque. The rear axle torque was not estimated, and the reference system did not include measurements of v x or ω z .…”

Section: Introductionmentioning

confidence: 99%

Active Control for an Electric Vehicle with an Observer for Torque Energy-Saving

González-López,

Pérez,

Betancourt

et al. 2023

WEVJ

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Vehicle dynamics play an important role in determining a vehicle’s stability. It is necessary to identify and obtain models related to vehicle dynamics to evaluate the performance of electric vehicles, as well as how to control them. This paper presents fundamentals of vehicle dynamics, proposing a three-degree-of-freedom nonlinear observer and controller to control lateral velocity and tire torque in comparison to a PID control, while also utilizing a Lyapunov function to determine the stability of the controlled state feedback system concerning the observer, which estimates state errors. This work demonstrates the mathematical development of estimations that will be fed into the algorithms of two active nonlinear controls (state feedback and PID), utilizing the results from Matlab-Simulink simulations of tire torque, lateral and angular velocities based on longitudinal velocity measurements, and employing dynamic gains, such as response to a steering maneuver by the driver following the international standards ISO 7401/2011 and ISO 3888-2. It is concluded that the observer is robust and exhibits energy-saving efficiency in tire torque, even under conditions of variable tire-ground friction.

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An Electronic Line-Shafting Control Strategy Based on Sliding Mode Observer for Distributed Driving Electric Vehicles

Cited by 10 publications

References 42 publications

Sliding Mode Control of an Electric Vehicle Driven by a New Powertrain Technology Based on a Dual-Star Induction Machine

Sliding Mode Control of an Electric Vehicle Driven by a New Powertrain Technology Based on a Dual-Star Induction Machine

Parameter Optimization of Model Predictive Direct Motion Control for Distributed Drive Electric Vehicles Considering Efficiency and the Driving Feeling

Active Control for an Electric Vehicle with an Observer for Torque Energy-Saving

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