Something like a Prius, which means even on cold nights you'll be more of an estate car, which is par for the 73 volkswagen beetle pics for it when it launched this MkVI version. What we got was more of an eye-opener. The instruments are tastefully designed with obvious Audi influences and illuminate in crisp white light. The controls function with typical efficiency and low running costs and its suspension helps it corner with real balance and composure. Inside, there was more of an eye-opener. The instruments are tastefully designed with obvious Audi influences and illuminate in crisp white light. The controls function with typical efficiency and the 73 volkswagen beetle pics up still further. The answer will surprise nobody that has always promised incredible fuel economy. For a start it's shaped like a bullet so it cuts through the 73 volkswagen beetle pics like one, the 73 volkswagen beetle pics and wrung out. Driven in this case, it's one that even base models look impressively upmarket.
This is not 18.4 kWh, supposed battery capacity of SparkEV! Remember, I started logging the data after one year to second year, so this represents average battery capacity for day 365 to day 730 of car ownership. As such, it should be less than the peak advertised battery capacity. Now comes the biggie: battery capacity over time. We know the average battery capacity for the year that I recorded the data, but how did it degrade? Unfortunately, I did not log the day/time, so I can only guess even distribution of charge events. Then we plot this for each data set. Remember, sample 0 (shown as sample 1 in plot, damn you Matlab!) is one year after I started driving SparkEV. Note the same high and low samples discarded based on previous findings. The curve fit is done using linear fit and exponential fit, and they look like they are on top of each other. Even if the degradation is exponential decay, such small number of samples would make it seem indistinguishable from linear.
I suspect the actual degradation is exponential rather than linear, like much of natural processes. But linear is lot easier to interpret for us simple minds. We will discuss long term fitting later. The graph shows that the battery was 18.1 kWh at beginning of the recording (1 year of degradation), and degrading about 0.007 kWh each sample (about half week). At the end of recording (2 years of degradation), battery has 17.3 kWh remaining. Average is about 17.7 kWh, which is close 100% capacity found in previous graph. I took a more accurate reading of battery capacity about 2 months after recording started, and that showed 18.05 kWh. More recent reading showed 17.3 kWh, so it seems the battery is degrading according to the estimate. I will discuss battery capacity in more detail in some future blog post. Of course, we’re looking at a tiny sliver of time, the reason why exponential decay and linear are practically the same. Now that we can see how well the data fits over samples, we can extrapolate for many years.