EV Planner Compared

Selgitus

Miks kaks planeerijat annavad samale autole erineva vastuse

Sama auto, sama sõidutee, sama päev. Üks ütleb kolm peatust ja kuus tundi, teine kaks peatust ja viis. Kumbki ei valeta — nad on eri meelt asjade suhtes, mis on tegelikult ebaselged.

Updated 2 min read 40 citations Evidence strength 3/5

Vaade kiirteele ülesõidusillalt väljasõiduteeramba suunas
Dietmar Rabich · CC BY-SA 4.0 · Wikimedia Commons

Nad eeldavad erinevaid kiirusi

Aerodünaamiline õhutakistus kasvab kiiruse ruuduga ja selle ületamiseks vajalik võimsus kiiruse kuubiga. Vahe 110 km/h ja 130 km/h vahel ei ole seega kahekümneprotsendine erinevus kulus – see on palju suurem. Planeerija, kes eeldab, et sõidate piirkiirusel, ja planeerija, kes eeldab, et jääte sellest pisut allapoole, modelleerivad kahte erinevat sõitu.

Enamik tööriistu lubab seda seadistada, kuid enamik inimesi ei tee seda kunagi. Kui kaks planeerijat on eri meelt ja saate kontrollida ainult üht asja, kontrollige eeldatavat kiirust.

Nad modelleerivad laadimiskõverat erinevalt või mitte üldse

Liitium-ioonaku võtab vastu suurt võimsust madala laetuse taseme juures ja laadimiskiirus väheneb järsult, kui aku täitub [3]. Praktikas tähendab see, et laadimise viimased kakskümmend protsenti võivad võtta niipalju aega kui esimesed viiskümmend, mistõttu optimaalne strateegia on tavaliselt rohkem, aga lühemaid peatusi, mitte vähem ja pikemaid.

Planeerija, mis seda korrektselt modelleerib, koostab marsruudi, mis näib ebaefektiivne – neli peatust kahe asemel –, kuid viib teid ikkagi kiiremini sihtkohta. Planeerija, mis käsitleb laadimist ühtlase kiirusega, koostab korrapärasema plaani, mis on vale.

Nad on eri meelt ilma osas

Külm vähendab kasutatavat sõiduulatust ja aeglustab samal ajal kiirust, millega aku laengut vastu võtab [4]. Mõlemad mõjud toimivad samas suunas, ja pehme ilma kulunormidele ehitatud plaan võib ebaõnnestuda viisil, mida väike veamarginaal ei kata.

See on rida, kus planeerijate vaheline erinevus on kõige olulisema tähtsusega, ja seepärast käsitleb võimekuste tabel ilmastiku modelleerimist esmatähtsa omadusena, mitte lisaboonusena.

Nad on eri meelt selles, kui palju peaksite kartma

Saabumisvaru – kui palju laengut planeerija nõuab, et teil peatusesse jõudmisel veel alles oleks – ei ole füüsikaline suurus. See on põhimõtteline valik. Tööriist, mis on seatud saabuma 10% juures, ja teine, mis on seatud saabuma 20% juures, koostavad identsetest sisenditest sisuliselt erinevad marsruudid, ning kumbki ei ole vale.

Sõiduulatuse ärevus on hästi dokumenteeritud mõjutaja sellele, kuidas juhid tegelikult käituvad, eraldiseisvalt sellest, mida auto suudab [5]. Planeerija, mis lubab seda seadistada, lubab teil hinnastada oma närve, ja see on õige koht, kus see otsus tegelikult peaks olema tehtud.

Mida sellega ette võtta

  • Seadke kiiruse eeldus vastavaks sellele, kuidas te tegelikult sõidate, mitte sellele, mida kavatsete.
  • Külmal päeval planeerige pessimistliku tööriistaga ja käsitlege optimistlikku kui parimat võimalikku stsenaariumit.
  • Usaldage planeerijat, mis pakub rohkem lühemaid peatusi, rohkem kui üht, mis pakub vähem pikemaid.
  • Planeerige uuesti sõidu ajal, mitte alguses. Selleks ajaks on kõik sisendid juba muutunud.
Kolmerealine briti kiirtee, liiklus mõlemas suunas halli taeva all
Klaus with K · CC BY-SA 3.0 · Wikimedia Commons

Seotud lugemine

Selle lehe aluseks olevad tõendid Virnastatud tulpdiagramm, mis näitab sellel leheküljel viidatud 40 publikatsiooni jaotust uuringutüübi kaupa. 40other (40)
40 publikatsiooni, 2012–2026. See on suures osas vaatluslik andmebaas. See saab tõestada, et nähtused esinevad koos; see ei suuda kindlaks teha, kumb põhjustab teist. Allikas: selle lehe oma viidete loetelu allpool.

References

Every citation below links to the original peer-reviewed record on PubMed or via DOI. Nothing here is a substitute for medical advice.

  1. Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data Iora P, Tribioli L · World Electric Vehicle Journal · 2019 · Journal article DOI
  2. Electric Vehicle Energy Consumption Modelling and Prediction Based on Road Information Wang J, Besselink I, Nijmeijer H · World Electric Vehicle Journal · 2015 · Journal article DOI
  3. Machine learning-based uncertainty quantification for energy consumption and driving range estimation in electric cargo vehicles Gandhi M, Chaudhari A · Energy Informatics · 2026 · Journal article DOI
  4. Estimation of Energy Consumption in Battery-electric Motorcycles Using a Virtual Vehicle Model and the Development of a Customized Measurement System Göntér Á, Sipos T · Periodica Polytechnica Transportation Engineering · 2026 · Journal article DOI
  5. Dynamic Electric Vehicle Route Planning via Traffic Flow Prediction and Charging Service Integration Zhang Y, Shen X, Wang Y · Processes · 2026 · Journal article DOI
  6. Optimizing Electric Delivery Vehicle Route Planning: A Hybrid Approach Integrating Clustering and Ant Colony Algorithm for Sustainable Transportation Heng S, Sharma A, Xiao J · Sustainability · 2026 · Journal article DOI
  7. Site and Capacity Planning of Electric Vehicle Charging Stations Based on Road–Grid Coupling Tian Z, Yan Q, Ma Y, et al. · World Electric Vehicle Journal · 2026 · Journal article DOI
  8. Modeling Electric Vehicle Adoption in Thailand: The Impact of Ecosystem and Policy Support via Perceived Value and Charging Anxiety Suvittawat A, Suvittawat N · World Electric Vehicle Journal · 2026 · Journal article DOI
  9. Revisiting Electric Mobility: How Individual Perceived Value Shapes Battery Electric Vehicle Adoption—Insights into Technophilia, Range Anxiety, and Battery Cost in China Jia H, Zhao H, Uchiyama Y · World Electric Vehicle Journal · 2026 · Journal article DOI
  10. Research on electric vehicle energy consumption prediction based on BP neural network Ding R, Zhao J · Advances in Engineering Innovation · 2026 · Journal article DOI
  11. MACHINE LEARNING-DRIVEN OPTIMIZATION OF ELECTRIC VEHICLE CHARGING WITH DRIVER SATISFACTION MODELING CHERUVU AYESHA, Mrs.B.JYOTHSHA, Mr.P. VISWANATHA REDDY · ETDT · 2026 · Journal article DOI
  12. Electric Vehicle Charging Station Location Planning Based on Range Anxiety in Last Mile Logistics in Yogyakarta Haryanto Z, Afraah S · Jurnal Teknologi · 2025 · Journal article DOI
  13. Systematic Planning of Electric Vehicle Battery Swapping and Charging Station Location and Driver Routing with Bi-Level Optimization Chen B, Chen J, Feng H · World Electric Vehicle Journal · 2025 · Journal article DOI
  14. Influencer-Mediated Range Anxiety Mitigation: Examining Social Media Marketing Pathways to Electric Vehicle Adoption in Vietnam's Digital Economy NGUYEN T · Journal of Economics, Finance And Management Studies · 2025 · Journal article DOI
  15. An Electric Vehicle Optimal Charging Path Planning based on an Improved A* Algorithm Chen X · Frontiers in Computing and Intelligent Systems · 2025 · Journal article DOI
  16. Optimisation of Electric Vehicle Charging Stations Planning Based on Macro and Micro Perspectives WANG Q, DENG K, YAN J, et al. · Promet - Traffic&Transportation · 2025 · Journal article DOI
  17. Personalised electric vehicle charging stop planning through online estimators Shafipour E, Stein S, Ahipasaoglu S · Autonomous Agents and Multi-Agent Systems · 2024 · Journal article DOI
  18. Integrated model construction for state of charge estimation in electric vehicle lithium batteries Liu Y, Dun W · Energy Informatics · 2024 · Journal article DOI
  19. Optimization model of battery electric vehicle charging facility layout towards embedded system and data mining algorithm Zhang P, Liu J, Luo N, et al. · International Journal of Emerging Electric Power Systems · 2024 · Journal article DOI
  20. Electric Vehicle Distribution Route Optimisation and Charging Strategy Considering Dynamic Loads Wu Q, Tian M · Polish Journal of Environmental Studies · 2024 · Journal article DOI
  21. Multi-Objective Electric Vehicle Route and Charging Planning with Contraction Hierarchies Cuchý M, Vokřínek J, Jakob M · Proceedings of the International Conference on Automated Planning and Scheduling · 2024 · Journal article DOI
  22. Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning Jayaram J, Chetan J, Nayak B · Journal of Informatics and Web Engineering · 2024 · Journal article DOI
  23. Electric Vehicle Charging Route Planning for Shortest Travel Time Based on Improved Ant Colony Optimization Tan A, Wang C, Wang Y, et al. · Sensors · 2024 · Journal article DOI
  24. Optimal number of charging station and pricing strategy for the electric vehicle with component commonality considering consumer range anxiety Yu W, Zhang L, Lu R, et al. · PLOS ONE · 2023 · Journal article DOI
  25. Electric Vehicle Charging Sessions Generator Based on Clustered Driver Behaviors Van Kriekinge G, De Cauwer C, Sapountzoglou N, et al. · World Electric Vehicle Journal · 2023 · Journal article DOI
  26. Charging after Lockdown: The Aftermath of COVID-19 Policies on Electric Vehicle Charging Behaviour in The Netherlands van der Koogh M, Wolbertus R, Heller R · World Electric Vehicle Journal · 2023 · Journal article DOI
  27. Evaluation of Electric Vehicle Charging Usage and Driver Activity Mahlberg J, Desai J, Bullock D · World Electric Vehicle Journal · 2023 · Journal article DOI
  28. Energy Cost Analysis and Operational Range Prediction Based on Medium- and Heavy-Duty Electric Vehicle Real-World Deployments across the United States Qiu Y, Dobbelaere C, Song S · World Electric Vehicle Journal · 2023 · Journal article DOI
  29. Research and Evaluation of Electric Vehicle Charging Station Layout Planning Based on Greedy Algorithm Yu C, Chen M, Lu H, et al. · Highlights in Science, Engineering and Technology · 2023 · Journal article DOI
  30. Simulation model for rendering and analyzing the prediction of electric vehicle energy consumption in Matlab/Simulink Janković F, Mujović S · ETF Journal of Electrical Engineering · 2023 · Journal article DOI
  31. Electric Vehicle Charging Station Location Model considering Charging Choice Behavior and Range Anxiety Liu H, Li Y, Zhang C, et al. · Sustainability · 2022 · Journal article DOI
  32. Electric Vehicle Range Estimation Using Regression Techniques Ahmed M, Mao Z, Zheng Y, et al. · World Electric Vehicle Journal · 2022 · Journal article DOI
  33. Rapid Evaluation Method for Accuracy of Range Estimation of Pure Electric Vehicle Range Estimation Based on CLTC-P Dai T, Zhou B, Zhang Y, et al. · E3S Web of Conferences · 2021 · Journal article DOI
  34. An Optimal Control Algorithm with Reduced DC-Bus Current Fluctuation for Multiple Charging Modes of Electric Vehicle Charging Station Chen T, Fu P, Chen X, et al. · World Electric Vehicle Journal · 2021 · Journal article DOI
  35. Research on Establishment of Vehicle Energy Distribution Model and Energy Consumption Optimization Based on Electric Hybrid System Liang P, He H, Cui H, et al. · World Electric Vehicle Journal · 2021 · Journal article DOI
  36. Optimization Approach for Long-Term Planning of Charging Infrastructure for Fixed-Route Transportation Systems Blat Belmonte B, Rinderknecht S · World Electric Vehicle Journal · 2021 · Journal article DOI
  37. Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling Pitanuwat S, Aoki H, IIzuka S, et al. · World Electric Vehicle Journal · 2019 · Journal article DOI
  38. Economic Microgrid Planning Algorithm with Electric Vehicle Charging Demands Yoon S, Kang S · Energies · 2017 · Journal article DOI
  39. Online Prediction of Battery Electric Vehicle Energy Consumption Wang J, Besselink I, Nijmeijer H · World Electric Vehicle Journal · 2016 · Journal article DOI
  40. Model-Based Remaining Driving Range Prediction in Electric Vehicles by using Particle Filtering and Markov Chains Oliva J, Weihrauch C, Bertram T · World Electric Vehicle Journal · 2013 · Journal article DOI

This page was translated automatically from English. The citations and numbers are unchanged. Read the English original if anything reads oddly. Read the English original