Evidence map›Paper›PMID 41230116›Full record

ArticleFrontiers in physiology2025

Optimization of physical energy and velocity allocation for cyclists in road cycling individual time trial using genetic algorithm.

Xinyu Li, Benxu Zou, Xin Wang, Chaoran Liu

Abstract read
In one paragraph

Article in Frontiers in physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xinyu LiShenyang Sport University, Shenyang, China.
Benxu ZouShenyang Sport University, Shenyang, China.
Xin WangShenyang Sport University, Shenyang, China.
Chaoran LiuHangzhou Dianzi University, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Effective energy management for optimizing energy and speed allocation for athletes in road cycling individual time trials is crucial due to the race's long distances. Existing strategies often consume excessive body energy due to inadequately addressing the impact of slopes and curves. Methods: We propose an advanced energy allocation strategy using a genetic algorithm. Our research focuses on optimizing speed and energy allocation specifically in curves and on slopes given factors such as air resistance, friction, gravity and weather to maximize athletes' energy efficiency during time trials. For curve optimization, we optimize the athletes' cornering strategies based on the parameters including road width, inner curve radius and curve angles. Results: The simulation results demonstrate that time is reduced by 9.7% on a standard 400-m track and time is reduced by 6.35% on bridge testing comparing with pre optimization strategies. Discussion: We validate the optimizing strategy based on the 2024 Paris Olympic Games road cycling individual time trial course, which demonstrates the effectiveness of the strategy. This research provides athletes with valuable guidance for optimal energy distribution.

Indexed as

cornersenergy and speed optimization strategygenetic algorithmroad cycling individual time trialsslopes

Identifiers

PMID41230116
PMCPMC12602211

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.