We are currently searching for a web developer to work with us on a part-time basis over two months. The objective is to develop an online web application for EV-Fleet-Sim. EV-Fleet-Sim currently is a simulation software that is run on a local machine, using a text-based interface (terminal).
We are therefore looking for a developer to deliver a web app which executes the various simulation steps of EV-Fleet-Sim through a user-friendly interface. The developer will be responsible for the design and development of the web-app, as well as specifying the API calls needed from the EV-Fleet-Sim backend. We, the client, will be responsible for the actual implementation of the API and backend services.
More detailed specifications will be provided on request or over the course of the contract.
The contract will commence on 19 February 2024, and the web app is to by completed by 19 April 2024. An additional “maintenance period” of two weeks after completing the project will also be governed by the contract. The remuneration for completing the project will be ZAR 15 000, including tax.
To apply, contact Chris Abraham (email) by 13 February 2024, or alternatively, visit our LinkedIn job listing.
Edit 2024-02-19: The position has been filled. Thank you to all who applied.
]]>Electric vehicles (EVs) are becoming extremely popular across the world. But few companies in Africa are willing to take the jump. EVs come with a whole host of uncertainties, including charging times, range anxiety, load-shedding impacts and electricity bills. This can make the transition challenging. The Stellenbosch University Smart Mobility lab has come to the rescue with their new EV-Fleet-Sim software.
Golden Arrow Bus Services (GABS) is one of the few South African companies that have started to find potential in EV technology. The company, which owns 1100 diesel buses in Cape Town, started investigating the technology in 2021 when they invested millions of rand to purchase two EV buses. The pilot study proved successful, and they have recently announced plans to purchase 40 EV buses per year!
Such success stories require high levels of planning, research and investment. Stellenbosch University’s EV-Fleet-Sim reduces this burden, by virtually simulating the EV fleet, rather than requiring companies to purchase real EVs to investigate their ideas.
In their recent study of minibus taxis, the team behind EV-Fleet-Sim, projected the daily electricity requirements of an EV taxi concept. Taxis were simulated as EVs and were found to require 120 units of electricity to travel 250 km per day. This allowed taxi owners to evaluate their profit margins & decide if the switch would be worth it.
Companies are not only worried about economic aspects however. They are also worried whether EVs would meet the technical needs of their fleet. In the example above, taxis required a battery size around double that of a typical Tesla EV battery. This proved to be feasible. However, this may not be the case for other vehicle fleets.
Additional questions that may be applicable include: whether the EV fleet would find sufficient opportunities to charge amidst their daily operations, and how big a solar installation would be required to combat the threat of load shedding. EV-fleet-Sim answers all these questions and more
With data collection and modern computational software to ease the transition to EVs, companies in Africa have fewer reasons to investigate EV technologies for their fleets. Visit https://ev-fleet-sim.online to see if EVs could be a solution to your transport needs.
]]>Why?
Poor electricity utility:
Extremely inefficient power-stations
Fossil fuels used in Transportation/Freight.
How can we fix these problems? We need better electricity and transport infrastructure.
Taxis carry > 60% of SA’s commuters!
Taxis often unsafe: not roadworthy because of poor maintenance, and sometimes overcrowded
Taxi routes & schedules are often unpredictable – you can stand in one spot for an hour waiting for a taxi
SA also suffers from poor electricity generation capabilities, and it is affecting economy negatively. Stage 2 Load Shedding Costs SA’s economy R40B per month!
Introducing a concept to save our future: Electric Taxis.
How it works:
Taxi ranks installed with solar panels.
Panels charge parked taxis and feed excess power to the grid.
Taxis use battery power to transport passengers in the afternoon/evening (peak transport hours).
In the evening (peak load hours), taxi is plugged into grid via driver’s shack, and battery supplies power to the grid.
If battery is depleted too much, it will be trickle charged from the grid during off-peak hours (early in the morning).
Taxis use battery power to transport passengers in the morning (peak transport hours).
Taxi returns to taxi rank by mid-day to get a quick charge from the solar micro-grid while passengers board.
My research is to evaluate the system’s feasibility and performance. I will use simulation & modelling, but will get a prototype (to-scale) built, if funding permits.
What is hoped from research outcomes: Despite a big initial investment, it is hoped that e-taxi solution will offset the costs to SA’s economy due to load shedding and the poor performance of existing coal power-stations. Taxi’s will have cheaper running costs (electricity is cheaper than petrol, and taxi will need less maintenance). Taxi’s will also be safer, and intelligent IOT systems can help passengers predict the time and place where they can hail a ride.
]]>I kicked off my research with the following question. If a country were to adopt a large-scale EV roll-out, how would they plan to charge all those EVs? Would that charging have a negative effect on the grid?
As it turned out, many countries are starting to adopt “smart-grids”, and “Vehicle-to-Grid (V2G)” systems. These systems are used to make use of vehicle batteries as distributed energy resources. In other words, the utility uses these systems to buy electricity from the EV owners during peak-load times at high rates (thereby drawing from their EV batteries), and sell electricity back during off peak times at low rates (charging the EV). This could actually be useful for SA’s load-shedding crisis while providing an extra passive income for taxi owners, but it will require substantial infrastructure investment.
I have also read on PV systems/micro-grids. Solar energy is becoming increasingly cheaper (e.g. thin-film technologies). At the same time it can stat to off-set the inefficient coal stations of South Africa. Unfortunately, solar energy is temporal, but if a sufficient number of taxis were deployed, batteries can be used to store that energy & resell it to the grid in the evening (peak electric load hours).
Two problems are posed by this, however. Firstly, who will buy all these taxis and scrap the old ones? Should it be phased in slowly, as old taxis are progressively take out of the market? Similar to the way Quantums have out-phased the old Hi-Aces? Sounds possible. Are “taxi-conversion kits” an option, or would that be too unreliable? Also that would leave too many waste engines. So far, I lean towards the former, more long-term, idea.
The reality is that within the next 20 years, these Quantums will become old and out of market. Trends indicate that manufacturers are phasing out petrol cars for electric. How will South Africa adapt to this, given its failing electric utility? Do we keep using petrol cars? One cannot predict the future with certainty, but the aforementioned envisioned future is certainly a viable possibility. As such, my research will evaluate this reality, by modelling the various actors & systems in place.
This is what I have done in that modelling process so far. I have identified a number of tools that simulate distributed energy resources (batteries & solar panels in this case), traffic simulation, and system block-diagram modelling/documentation. I further plan to find simulation tools for modelling the electric vehicle, pedestrian demand, micro-grid, and EV charger. I am looking at open-source tools so that my research outputs can be widely and easily accessible for the scientific community.
Although my goal is not to “culturally engineer” society to think in my proposed paradigm, I do feel that it is relevant to engage with the general public to obtain their feedback on this idea, so that my concept can be: 1. seeded in their minds, 2. adaptable to their needs, 3. not forced upon them in an inefficient way filled with misinformation & resulting in retaliation. As such, I will hopefully get feedback from the taxi industry as well as passengers. I hope to stick flyers in taxis which link to website where people can cast their vote or opinions on the matter.
This qualitative data may be useful in identifying the roadblocks and opportunities that define the path to this conceptual future reality. However, quantitative data is also essential to this study. How do current driving patterns of taxi drivers, passenger demand patterns, electricity demand patterns (on the grid), solar resource availability patterns (annually and daily) , and other quantitative patterns affect the performance of this future system? Of course, certain assumptions may have to be made when using this data. Can it be used “as-is” or will it have to be “transformed” based on trends to match future predictions of these patterns? In any case, I plan to input this qualitative data into a software which ties together all the aforementioned modelling toolkits to simulate the performance (economically, environmentally) of this hypothetical reality. This software will be a research output that can be used by any African city (many of which are using minibus taxis) to evaluate the performance in their region. My research paper will narrow the scope to Cape Town or South Africa.
This entry has summarized my thoughts on the topic. A lot lies ahead on this roadmap. Reading, analyzing existing software, scripting of interfaces and tweaking source code. At the same time, i want to create a presence in the general public & scientific communities. I want to obtain qualitative data in the form of public opinion, as well as quantitative data in the various forms discussed. I’m looking forward to this project.
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