Optimization of Hybrid Vehicle Driving

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F17%3A00320917" target="_blank" >RIV/68407700:21220/17:00320917 - isvavai.cz</a>

Result on the web

<a href="http://fs12120.fsid.cvut.cz/softlib/2017/HybridOptimization.zip" target="_blank" >http://fs12120.fsid.cvut.cz/softlib/2017/HybridOptimization.zip</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Optimization of Hybrid Vehicle Driving

Original language description

The predictive optimization of minimum energy consumption and low carbon dioxide emissions at known route is becoming the standard tool for the extended horizon driving control of hybrid vehicles. The problem occurs if the capacity of accumulators is sufficient for distance much longer than the extended horizon is. The driving strategy should assess the possibilities of re-charging an accumulator for the optimum combination of prime mover power (today, an internal combustion engine) and an electric motor power booster, taking the rest of trip into account. Adaption for changed traffic density or weather is the next step of future control systems, finding the best compromise between trip time and total energy consumption. The “brute force” optimization of many thousands independent variables for the model with detailed description of vehicle components is possible, if performed out of real time only, using dynamic programming techniques and cloud computing devices. The paper describes fast model and optimization algorithm for the best carbon dioxide emissions, which finds the local optimum distribution of power between an engine and a motor/generator, applying the numerical solution for finding the optimum of energy consumption, described by a regression powertrain model. It takes the efficiency of stored electric energy use in a motor during the relevant rest of trip into account by iterative way. The model limits number of optimization variables by semi-heuristic algorithm of speed schedule in a route section. Then, the eco-driving optimization can be done by genetic algorithm. Currently, the model describes single-accumulator parallel or serial hybrids including differential power splitter, but it can be extended to all hybrid layouts.

Czech name

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Czech description

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Type

R - Software

CEP classification

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OECD FORD branch

20302 - Applied mechanics

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Internal product ID

HybridOptimization

Technical parameters

Smlouva o využití výsledků uzavřena s Honeywell spol. s r. o., Ricardo Prague s.r.o., TÜV SÜD CZECH s.r.o., TU v Liberci, VŠB TU Ostrava, VUT v Brně v rámci využívání progrmaové náplně DASY a OntoDASY. MS EXCEL, 150 MB. Rozsáhlý program pro optimalizaci průjedu zadanou trasou. Velikost podle rozsahu trasy.

Economical parameters

Náklady na vývoj programu 2,2 MKč. Licence zdarma, pokud provozován na serveru ČVUT. Program poskytnut zahraničním partnerům v projektech H2020.

Owner IČO

68407700

Owner name

FS - rezerva