When selecting an EV, one is offered to choose between various battery packs. Today, batteries are offered on the basis of the range they can deliver. Longer range or faster cars correspond to larger batteries made of more of the same unit cell. However, these batteries do not distinguish between different use-cases. Below are three among many examples of urban EV use cases.
Case 1: the privately owned EV
The car will be used mainly in the city and will be charged one to two times a week. Either at home or at work but will remain parked a vast majority of the time. Short irregular cycles with a lot of neutral stress (slow leakage) time
Case 2: the taxicab EV
The vehicle needs to be able to drive all day with minimal to no stopping. Will be very often in traffic or at low speeds within cities. Ideally it is parked all night and plugged-in to charge for the following shift.
Case 3: the free-floating EV
With systems like ZipCar, Moovin in Paris or it's ancestor Autolib', vehicles are submitted to high frequency of short cycles of charge and discharge.
In all these cases, the batteries in the vehicle are submitted to a high variety of stresses and strains and with no adapted battery structures, these are bound to fail rapidly.
Addionics take on the topic:
Addionics' high capabilities of fine tuning combined with our Machine Learning algorithms and large testing cycles allow our solution to fit the end user's charging habits at best and guarantee a longer lifetime and improved safety for batteries.
This ambitious claim raises many questions. In particular, at which stage of the supply chain to implement the customisation? On what scale? And how would second hand market function?
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