Insights gained from owning an Electric Vehicle (EV)

Hi there — I bought a Kia Niro EV in March 2022.  Some top-line specs:

  • 64 KWh battery
  • EPA range of 239 miles
  • DC fast-charging capable
  • Charging ports: SAE J1772 for AC charging, and Combined Charging System (CCS), for DC fast charging
  • Automatic car following and lane keeping
  • Heat pump for heating/cooling

And here are some things that I learned — somewhat in order of learning them …

  1. The EV world has a standard way of defining three charging scenarios:
    • Level 1 – this is typically 110V AC, up to about 12 amps, about 1300 Watts charging power.  Mathematically would take battery from empty-to-full in 64 KWh/1.3 KW = 49 hours
    • Level 2 – this is typically 220V AC, up to about 30 amps, about 6.6 KWatts.  Mathematically would take battery from empty-to-full in 64 KWh/6.6 KW = 9.7 hours.  Actual time would be longer, as the top-off part of the charge will be a lower rate.
    • Level 3 – this can be up to 150 KW, delivered via direct current (DC), but my Kia can only accept up to 100 KW.  Mathematically would take battery from empty-to-full in 64 KWh/100 KW = 38 minutes.  Actual time would be longer, as the top-off part of the charge will be a much lower rate.  But can realistically add 200 miles of range in 26 minutes.
  2. Just about every EV comes with an extension cord that allows you to plug the car into any home outlet, and charge at Level 1.  This would be sufficient for any user who drives less than 45 miles/day on average (16,000 miles/year).
  3. TCNJ has ten Level 2 EV charging stations that are available to all permitted cars, for no fee.  When school is in session, all ten are full, Monday through Friday, by about 9:30 am.  Cars are permitted to charge for up to 4 hours, but that does not seem to be enforced.  Many users have pluggable hybrid cars (PHEVs), which charge up quickly, but stay plugged in for many hours.
  4. TCNJ EVs include Prius, Jeep and other PHEVs. Battery-only EVs (BEVs) include Ford Mustang EV, Hyundai Ioniq, Hyundai Kona, Jaguar, Chevy Bolts, several Teslas and my Kia Niro EV.
  5. It is easy to plug in an EV, but hard to unplug 🙂  I found out, the hard way, that EVs have an interlock that prevents hooligans from surreptitiously unplugging a car before it is fully charged.  On mine I have to use the key fob to unlock all doors, to unlatch the charging cable.  I’ve heard from other EV owners who were also challenged by this, and had to figure out how this works.
  6. I can get a range of over 300 miles on my 239-mile rated car if I drive under 50 MPH, don’t use climate control, and the ambient temperature is not very cold.
  7. Fuel efficiency on an EV is typically measured at miles-per-KWh (FYI – KWh is an abbreviation for kilowatt-hours).  I can get up to 5 miles per KWh, which would translate to a driving range of 64 KWh x 5 = 320 miles.  It’s easy once you know what to expect.
  8. To achieve full fuel efficiency in stop-and-go driving, I use one-pedal mode, where I avoid using the brake pedal to come to a stop.  In my car letting off on the accelerator will cause the car to decelerate rapidly, and I can bring the car to a complete stop by squeezing a paddle on the left side of the steering wheel.  This method can stop the car in about 10 feet when the speed is less than about 15 MPH.  Initially, I would keep a foot prepared to hit the brake pedal if this didn’t work fast enough, but I’ve developed a good sense of how quickly the paddle can bring the car to a stop.
  9. One pedal mode is super convenient for going around turns.  Instead of alternating between brakes and accelerator, the entire turn can be controlled using the accelerator pedal.  The ride is more comfortable and you can safely round curves much faster.
  10. The car sounds like the Starship Enterprise at speeds less than 15 MPH.  I initially assumed that this was a natural sound of the motor system, but the car has a noise generator to warn pedestrians that an otherwise quiet vehicle is approaching.  Likewise a loud beep is emitted when backing up.
  11. My Kia does not allow much customization — to disable the seatbelt alarm I had to buy a buckle extender.  I can’t reduce the volume of the backup alarm, or change the boot sounds, or low-speed warning sound.
  12. EV chargers are everywhere, but fast chargers are not yet everywhere.  For my long trips to Philadelphia, or to the Jersey shore there are convenient fast charge stations in Fishtown, Philadelphia and at the Atlantic City Expressway Farley rest stop.
  13. Fast charging costs about 20 cents/KWh, which is not much of a markup over retail.  At that price travel costs about 4.4 cents/mile, and use of home charging would cost 4 cents/mile.  For comparison, at $4.50/gallon for gasoline, a car that gets 25 MPG would cost about 18 cents/mile, or 4.5 times more.
  14. Driving 12,000 miles/year would cost $480/year in electricity, vs. $2160 for a car that gets 25 MPG.  EV savings is about $1600/year.
  15. EVs require little maintenance.  There is no transmission, no engine oil, no starter motor, no radiator, and brakes will last forever.  There is a Tesla battery pack that has gone almost 1 million miles.  And EV engines can also be expected to reach 1 million miles.


Links on Machine Learning/Deep Learning/Convolutional Neural Networks

Textbook is available (but only printable/downloadable by chapter) here:

Deep Learning, by Ian Goodfellow and Yoshua Bengio, MIT Press, 2016

Other links of interest:

Intelligent Media Processing Laboratory – Ongoing Research Projects

Hi ECE Students — I welcome all of you to participate in one or more of my research projects.  In order to contribute you should be motivated to learn and explore.  Some of my projects have funding for student research salaries — job openings will be posted and announced.

My projects include:

  • Convolutional neural networks (deep learning)
    • Character-based tweet classification
    • Computer vision for robotic applications
    • Image colorspace analysis
    • Retrieval of “similar” images from among a collection
  • Video compression
    • New and improved algorithms for video compression
    • Interaction between image/video compression and computer vision
  • Digital chip design/computer engineering
    • Use of High Level Synthesis for modeling, implementation and verification of circuits for compressed video

I am also willing to supervise research in other areas where I have expertise, including embedded systems, digital signal processing, digital music, adaptive filtering, active noise cancellation, probability and statistics and digital communication.

If you have interest please contact me at  I look forward to your joining our team!


Video Compression, Information Theory, and the Central “Intelligence” Agency

A few weeks ago, in ELC 470 class, I spoke in vague terms about a compression hoax that I investigated as part of a due-diligence effort, while employed at ATI Technologies (ATI subsequently merged with AMD, the company that makes the chips in your PC).  A friend of mine will soon be joining Intel in Portland, and this prompted me to see if I could dig up more information on this topic (it involved Intel’s video “home” group in Portland).  It turns out that this was the early-ish part in the history of an elaborate scam that wound up getting millions from the CIA, and reportedly nearly had civilian planes shot down!  My report on the company strongly suggested that there was a hoax being perpetrated, but at the time I didn’t have enough information to prove it beyond doubt.  The hucksters skillfully avoiding saying too much, and never returned requests for compression samples to analyze.

A partner at ATI who joined me in the due diligence investigation reported back enthusiastically on the promise of the technology.  The positive response that this hoax received from highly intelligent people was pretty amazing and scary, considering that there had been a number of fairly well-publicized video compression scams during the previous decade.

I don’t really know how the compression scam morphed into the intelligence scam, but my vague recollection is that the compression scam was pre-9/11.  So the advent of 9/11 probably gave the scammers an opportunity to deftly weasel away from the Intel racket (which would likely have blown up shortly), and start fresh with the CIA.

Here’s some info from an article in “The Register”:

A long and highly entertaining Playboy article explains that in 2003, 50-year-old Dennis Montgomery was chief technology officer at Reno, Nevada-based eTreppid Technologies. The firm began as a video compression developer, but Montgomery took it in new and bizarre directions.

He reportedly convinced the CIA that he had software that could detect and decrypt “barcodes” in broadcasts by Al Jazeera, the Qatari news station.

The Company was apparently impressed enough to set up its own secure room at the firm to do what Montgomery called “noise filtering”. He somehow produced “reams of data” consisting of geographic coordinates and flight numbers.

In December 2003, it’s claimed CIA director George Tenet was sufficiently sold on Montgomery’s data to ground transatlantic flights, deploy heavily armed police on the streets of Manhattan and evacuate 5,000 people from the Metropolitan Museum of Art.

Homeland Security secretary Tom Ridge told the press the terror alert was the result of “credible sources – about near-term attacks that could either rival or exceed what we experienced on September 11”.

And more is detailed in a book: (Links to an external site.)


Another interesting article at: (Links to an external site.)

The C.I.A. never did an assessment to determine how a ruse had turned into a full-blown international incident, officials said, nor was anyone held accountable. In fact, agency officials who oversaw the technology directorate — including Donald Kerr, who helped persuade George J. Tenet, then the director of central intelligence, that the software was credible — were promoted, former officials said. “Nobody was blamed,” a former C.I.A. official said. “They acted like it never happened.”

Hello TCNJ!

I am delighted to be joining the distinguished academic community at The College of New Jersey.  In the 2014 Fall Term I am teaching:

  • ELC 383 – Electronics II
  • ELC 411 – Embedded Systems

and in the 2015 Spring Term I am teaching:

  • ENG 312 – Digital Circuits and Microprocessors
  • ELC 470 – Digital Video Processing and Compression

I am the director of the newly established TCNJ Intelligent Media Processing Laboratory (IMPL), which will involve research in the following areas:

  • Computer Vision
  • Processing of stereo and multi-view video
  • Digital video picture quality enhancement
  • Audio/video synchronization
  • Recovery of missing information from image sequences
  • Adaptive audio processing
  • Video compression

Please feel free to contact me about the possibility of joining my research program — opportunities for summer support under the Mentored Undergraduate Student Experience (MUSE) program and/or course credit via the research track are available.