Overview of the Project
My group and I created a mathematical model to minimize Singapore’s annual carbon emissions by optimizing the combination of vehicle power types used every year.
Problem Statement
The Singapore Green Plan 2030 targets nationwide long-term net-zero emissions by 2050. The Land
Transport Authority (LTA) of Singapore aims to reduce emissions from land transport by 80%. One way it has tried to achieve this aim is through the introduction of electric vehicles (EVs) and providing incentives for the private transport sector to adopt them. While EVs may have significantly lower carbon emission rates compared to their internal combustion engine (ICE) counterparts, they may produce considerably higher emissions during their production phases. With advancements in technology, EVs and hybrid vehicles have the potential to become even more efficient and sustainable. As such, the adoption of electric vehicles is an issue that Singapore must address.
Our problem statement is summarised as follows: How might we develop a mathematical model to predict the right combination of EVs, ICE, and hybrid cars to minimise the total carbon emissions of private transportation in Singapore?
Results
The model adapts easily to additional types of cars, scenarios and changes in car efficiency over time. However, it relies on sparse data from all over the world, which may not be applicable to Singapore’s context. Current trends in emissions may also not hold in the long term. The model does not account for future changes in Singapore’s energy sources too, which may cause EVs to seem less ideal than they might otherwise be. With more complete data and more time, the model can be adapted to become much more accurate.
Key Learning Points
- This was a good opportunity for us to create and assess our own mathematical model. At the same time, we also went an extra mile by creating a Python program to apply our model.
Attachments
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