Optimization Approach to Handle Global CO2 Fleet Emission Standards

2016-01-0904

04/05/2016

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
A worldwide decrease of legal limits for CO2 emissions and fuel economy led to stronger efforts for achieving the required reductions. The task is to evaluate technologies for CO2 reduction and to define a combination of such measures to ensure the targets. The challenge therefor is to find the optimal combination with respect to minimal costs. Individual vehicles as well as the whole fleet have to be considered in the cost analysis - which raises the complexity. Hereby, the focus of this work is the consideration and improvement of a new model series against the background of a fleet and the selection of measures. The ratio between the costs and the effect of the measures can be different for the each vehicle configuration. Also, the determination of targets depends whether a fleet or an individual vehicle is selected and has impact on the selection and optimization process of those measures. Nevertheless, balancing the boundary conditions and additional targets like driving performance is crucial. The effect and the need for the integration of such interactions into the optimization approach is demonstrated.
Using an integrated model-based approach, the presented research aims to combine the complexity of a complete vehicle simulation focusing on CO2 emissions and the challenge of optimizing the emissions of a vehicle fleet including cost aspects. The optimization algorithm has to handle the target requirements for the fleet as well as for the individual vehicle in accordance with boundary conditions for driving performance, target conflicts and interactions between the selected measures.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-0904
Pages
14
Citation
Martin, M., Eichberger, A., and Dragoti-Cela, E., "Optimization Approach to Handle Global CO2 Fleet Emission Standards," SAE Technical Paper 2016-01-0904, 2016, https://doi.org/10.4271/2016-01-0904.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-0904
Content Type
Technical Paper
Language
English