Electric cars are interesting for a variety of reasons that I won't belabor here (get in touch if you want more information). Like any major automotive technology the time scale to get to large numbers is quite long. We're probably to the point where things get interesting in a bit under a decade plus or minus a couple of years.
Several different classes of vehicles have emerged. The so called megacity cars are probably the most interesting as that is where most of the growth in the industry is likely to occur over the next few decade - think of iPads vs PCs... Both are around, but one is growing quickly. Of course time scales are different in these two industries.
The megacity cars will be lightweight and many are being designed with physics in mind - namely you worry about stop and go driving and dealing with acceleration. That means keeping weight to a minimum, controlling acceleration preferably using an electric motor rather than an IC engine, regenerative braking and so on. For higher constant speeds - say anything above about 40 mph, weight isn't an important factor but air resistance is. In addition to these huge areas of slipperiness and weight there are a few other loads like rolling resistance, a/c and (in EVs) heating loads, lights and even the vehicle's electronics.
Like any engineering problem there are several - in this case a boatload - of variables that need to be optimized. Many of these are non-independent and some, aestics for example, are cross-disciplinary. There is no such thing as a perfect car and the optimization of the design is close to an artform.
Vehicle efficiency is increasingly important and a standardized test procedures exist. One of the more interesting suite of tests are chassis dynamometer tests specified by the EPA. Cars are placed on full chassis dynamometers with the rollers adjusted to simulate the effects of weight and air resistance (the later is determined from separate coast-down tests where a car's coasting performance from fixed speeds is measured). The task is to follow a prescribed acceleration and braking pattern. The one that will follow has 23 starts and stops simulating city stop and go driving including an excursion to a bit over 55 mph.
What follows is some data from the Edison2 electric vehicle. A very light weight four passenger car with extremely slippery aerodynamics. It won the automotive X-prize with an internal combustion engine and now an electric version has been made. Really interesting as electrics are naturally about four times as efficient as IC vehicles.
The first graph shows the power drawn from the battery on the vertical axis in watts vs speed in mph on the horizontal axis. There is a lot going on and the power load is anything but constant in most places. Notice how the excursion to 55 mph uses a lot of power during the acceleration phase, but that drops off as the car is accelerating more slowly approaching its target. Also notice that the power demand barely exceeds 15 kW once and then only by a bit. The drive train and electronics are at last 80% efficient in this car, so the power to the wheels is even less. 15 kW is only about 20 horsepower. At speed the car is under 10 kW. An IC engine in the same car with its great aerodynamics and light weight would need about four times as much power.
Also note the area of negative power use. That's regenerative braking. Instead of turning the kinetic energy of the car into heat, some of the energy is converted to electricity by a generator and is used to recharge the battery a bit. The flatness of the line is probably a mechanical limitation on the generator or its controller. It has reached a very uniform limit.
The second graph is really neat. Rather than the continuous plot a time series of points representing the speed and power drain is shown. I would have done it a bit differently as points might appear on top of one another with a bit of information being lost, but with this limited amount of data that is probably not too much of a bias.
Now you can see at a glance where the vehicle lives in power/speed space by looking for densely populated regions. Notice the contribution from the regenerative braking doesn't seem to stand out as much and there is a very dense cluster at medium speeds that is mostly below 5 kW. This informs the design and give some clues to how you might optimize the design. The bursts to hither power levels are relatively rare - if you were doing a hybrid or were worried about battery costs you might be tempted to use ultracapacitors for bit of additional help. The fact that the vehicle don't spend a lot of cluster density during braking tells you maybe the design of that functionality doesn't need to be as perfect as you might have concluded from the first graph.
It should be noted that these curves are somewhat different in character and often very different in scale for conventional IC cars and different types of hybrids. They are approximations of "normal" parts of driving. The "nut behind the wheel" has a good deal of influence and the standards don't address that. It is remarkable how much can be gained if you can change driving behavior - the equivalant of thousands of dollars of technology for nothing. Sadly the technology game is much easier. Ideally you would do both.
You need to play with the information to learn what it can say. A variety of techniques is often necessary to shine a bit of light on what is really taking place. Of course this is true in almost anything where measurements are being made. You need to sweat the details and understand where the numbers came from, how the resulting information is manipulated and finally a lot of play can take place during the analaysis of the information. Frequently experience elsewhere gives the insight you need to notice curious things that other's might miss.
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