Fast velocity trajectory planning and control algorithm of intelligent 4WD electric vehicle for energy saving using time‐based MPC

Wu, Dongmei; Li, Yue; Du, Changqing; Ding, Heng; Li, Yang; Yang, Xiaobo; Lu, Xinyue

doi:10.1049/iet-its.2018.5103

Cited by 33 publications

(19 citation statements)

References 34 publications

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“…A comparison between an ALC based on DP with a spatially defined problem and an ALC based on model predictive control (MPC) with a temporally defined problem regarding the energy consumption of a battery electric vehicle (BEV) and the computation time is conducted in [9]. In simulations the vehicle requires 1.14% and 1.27% less energy with MPC ALC than with a proportional-integral-derivative controller that represents human driving behavior.…”

Section: Driver Assistance Systems For Automated Longitudinal Controlmentioning

confidence: 99%

“…For small slope angles cos(α) ≈ 1 applies, hence we can approximate the rolling resistance by the rolling resistance contant F 0 . Furthermore, the inertial force and climbing force can be merged using (9). The traction force F trac can be computed as…”

Section: Adaptive Traction Force Modelmentioning

confidence: 99%

“…vhcl includes an unseparable product ofv vhcl,x and v vhcl . For negligible road slope angle, v vhcl andv vhcl,x coincide with the model inputs v vhcl and a x because of (9). Therefore the linear model structure used in Section 3.3 for the ATFM is not suitable for the AEPM.…”

Section: Adaptive Electrical Power Modelmentioning

confidence: 99%

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Automated Longitudinal Control Based on Nonlinear Recursive B-Spline Approximation for Battery Electric Vehicles

Jauch

Bleimund

Frey

et al. 2019

WEVJ

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This works presents a driver assistance system for energy-efficient ALC of a BEV. The ALC calculates a temporal velocity trajectory from map data. The trajectory is represented by a cubic B-spline function and results from an optimization problem with respect to travel time, driving comfort and energy consumption. For the energetic optimization we propose an adaptive model of the required electrical traction power. The simple power train of a BEV allows the formulation of constraints as soft constraints. This leads to an unconstrained optimization problem that can be solved with iterative filter-based data approximation algorithms. The result is a direct trajectory optimization method of which the effort grows linearly with the trajectory length, as opposed to exponentially as with most other direct methods. We evaluate ALC in real test drives with a BEV. We also investigate the energy-saving potential in driving simulations with ALC compared to MLC. On the chosen reference route the ALC saves up to 3.4% energy compared to MLC at same average velocity, and achieves a 2.6% higher average velocity than MLC at the same energy consumption.

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Section: Driver Assistance Systems For Automated Longitudinal Controlmentioning

confidence: 99%

Section: Adaptive Traction Force Modelmentioning

confidence: 99%

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Automated Longitudinal Control Based on Nonlinear Recursive B-Spline Approximation for Battery Electric Vehicles

Jauch

Bleimund

Frey

et al. 2019

WEVJ

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show abstract

“…In condition of slipping mode, the torques ( 1,2,3) ci T i = transferred by the three friction elements are kinetic friction torques ki T that can be calculated as follows: Neglect the moment of inertia of the driving plate in the ball-cam mechanism, the compression force applied on the secondary clutch and the third friction element is,…”

Section: Torque Transfer Model For Slipping Modementioning

confidence: 99%

“…Although electric all-wheel drive vehicles have been a hot topic recently [1][2][3][4][5], the majority of the market share still vests in traditional mechanical AWD vehicles. The last few years have witnessed the evolution of the three generations of EMTC, the high fuel economy and excellent AWD performance make it widely used in many AWD cars, see Figure 1.…”

Section: Introductionmentioning

confidence: 99%

Electromagnetic Hysteresis Based Dynamics Model of an Electromagnetically Controlled Torque Coupling

Feng

Chen

et al. 2019

Processes

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This paper proposes a novel computationally efficient, easy-to-implement electromagnetic hysteresis based dynamics model of a kind of intelligent electromagnetic torque controlled coupling (EMTC), which, with drag torque under consideration, first models the electromagnetic hysteresis existing in the primary clutch with the classical Preisach model, and then models the transferred torques in the three friction elements of the center coupling in the slipping and locked modes, respectively. The performance of the model is verified by simulation and experiment jointly, which lays the basis for the development of advanced control algorithm.

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Integrating Dynamic Limiting Mechanism in Electric Scooters to Mitigate Range Anxiety via SoC-Tracking Range-Enhancement Attachment (STRETCH)

Kamarudin,

Zulkifli,

Abro

2023

Communications in Computer and Information Science

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Fast velocity trajectory planning and control algorithm of intelligent 4WD electric vehicle for energy saving using time‐based MPC

Cited by 33 publications

References 34 publications

Automated Longitudinal Control Based on Nonlinear Recursive B-Spline Approximation for Battery Electric Vehicles

Automated Longitudinal Control Based on Nonlinear Recursive B-Spline Approximation for Battery Electric Vehicles

Electromagnetic Hysteresis Based Dynamics Model of an Electromagnetically Controlled Torque Coupling

Integrating Dynamic Limiting Mechanism in Electric Scooters to Mitigate Range Anxiety via SoC-Tracking Range-Enhancement Attachment (STRETCH)

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