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Niaona Zhang

dblp:233/6072 · DBLP profile ↗
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3ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0001-7530-3960ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems
automotive embedded systems
0.312018
Optimization of gearshift MAP based on DP for vehicles with automated transmission · Sci. China Inf. Sci. 2018
Algorithms and data structures
dynamic programming
0.112018
Optimization of gearshift MAP based on DP for vehicles with automated transmission · Sci. China Inf. Sci. 2018

Methods — techniques the papers use, named apart from their topics

dynamic programming · 0.7
YearPublicationVenuePosition
2021 Time-Domain Predictable Trajectory Planning for Autonomous Driving Based on Internet of Vehicles
Qiuxin Song, Zonghao Li, Niaona Zhang, Jiasen Xu
BROADNETS4
2018 Optimization of gearshift MAP based on DP for vehicles with automated transmission
Lulu Guo, Bingzhao Gao, Niaona Zhang, Chuanxue Song
Sci. China Inf. Sci.5
2017 The electronic differential terminal sliding mode control based on genetic algorithm
abstract
In order to realize the differential function of electric vehicle driven by two rear wheel-hub motors, by following the optimal slip ratio of each wheel and equalizing the slip ratio of both drive wheels as target, a electronic differential control strategy based on terminal sliding mode is proposed. First of all, according to the standard μ-λ curve, the optimal slip ratio of the pavement is determined. Then, the deviation between the actual slip ratio and the optimal one is selected as the input variables. Based on the terminal sliding mode variable structure control theory, the electronic differential control strategy is designed to control the two rear wheel drive torque to achieve the function of electronic differential. At the same time, in order to further improve the performance of the system, the genetic algorithm is used to optimize the parameters in the terminal sliding mode algorithm. The simulation results show that the method proposed in this paper can realize the differential function and improve the stability of the electric vehicle.
Niaona Zhang, Wenjing Niu
IECON1