2020
DOI: 10.3390/electronics9081277
|View full text |Cite
|
Sign up to set email alerts
|

Battery Energy Management of Autonomous Electric Vehicles Using Computationally Inexpensive Model Predictive Control

Abstract: With the emergence of vehicle-communication technologies, many researchers have strongly focused their interest in vehicle energy-efficiency control using this connectivity. For instance, the exploitation of preview traffic enables the vehicle to plan its speed and position trajectories given a prediction horizon so that energy consumption is minimized. To handle the strong uncertainties in the traffic model in the future, a constrained controller is generally employed in the existing researches. However, its … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1

Citation Types

0
3
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7

Relationship

1
6

Authors

Journals

citations
Cited by 11 publications
(3 citation statements)
references
References 33 publications
(34 reference statements)
0
3
0
Order By: Relevance
“…Therefore, it can be seen that if φ → 0 , the tracking error e converges to 0 as t → ∞ [20]. Considering that highgain feedback with a too small φ can significantly degrade the smoothness of the control action, an appropriately small value was chosen as the boundary φ by the cost optimization technique for offline gain tuning [21].…”
Section: Model-based Controllermentioning
confidence: 99%
“…Therefore, it can be seen that if φ → 0 , the tracking error e converges to 0 as t → ∞ [20]. Considering that highgain feedback with a too small φ can significantly degrade the smoothness of the control action, an appropriately small value was chosen as the boundary φ by the cost optimization technique for offline gain tuning [21].…”
Section: Model-based Controllermentioning
confidence: 99%
“…One of the aspects that is becoming increasingly important is energy efficiency. With it come different approaches, from the design and development of better power supplies [27], to the improvement of batteries for electric vehicles [28].…”
Section: The Present Issuementioning
confidence: 99%
“…Meanwhile, the model predictive control (MPC) can be considered, which solves the finite time optimization problem in a receding horizon control manner [21]. Additionally, MPCbased vehicle short-term trajectory planning has confirmed its effectiveness in some literature [22], [23].…”
Section: Introductionmentioning
confidence: 99%