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Random thoughts on a sunday

The past couple months have been tough. Product development is easy but then understanding the problem and coming up with a solution is a bit tough. I’ve got an amazing highly motivated team with me. Built them up from scratch, no hi-fi engineers or management people from the big name colleges. Figure I’m not going to be a good teacher unless I train the local talent around me. The goal is that we become the best damn engineering team in South Asia in 2-3 years time.

Staying positive while at the garage and the office is a fight. Luckily my friends keep my spirits-up on chat, or my mom and dad do it everyday, it’s a whole lot of fun seeing support from unexpected places.

Sales visits are always an adventure. Got in touch with some old pals during the recent Bangalore visit. I was so tired and didn’t catch enough sleep for many hours straight, as you can see.

I guess in a startup, the game is about staying positive, keep in touch with everyone and just treating everyday like an adventure. It’s adrenaline the morning I wakeup at 6am and the night I finish at 11pm.



The power of algorithms

Algorithms and the software/firmware that they create have taken-up no.1 importance in the list of portfolio offerings for companies, followed by electronics, IoT, hardware, manufacturing and trading. Evidence of this is the format of patents being granted currently, with the general environment of the patent being drafted around the algorithm in a majority of cases. Not long ago, patents were only granted for hardware-based inventions with its corresponding software taking lesser importance. Things have changed since.

Some algorithms, like those that compute the Fibonacci sequences, are intuitive and may be innately embedded into our logical thinking and problem solving skills. However, for most of us, complex algorithms are best studied so we can use them as building blocks for more efficient logical problem solving in the future. ” – author of The importance of algorithms

The following are some of various deliverables that justify the power of programming code:

  • To control hardware- Reduce lead time, operational costs, increase efficiency, achieve automation, device data security, ease-of-use on the field, 1-platform framework, field diagnosis, testing, standards compliance etc.
  • To streamline operations & execution for non-technical abstract operational problems (ex.: audit).
  • To address everyday common user problems- Ease-of-use, productivity, happiness quotient, etc. (ex.:smartphone-based).
  • To predict trends- market, finance, banking, valuation etc.
  • Game theory, pattern prediction etc.

An example case to control hardware:

To control hardware:

Robots welding in a pre-programmed pattern is a common manufacturing practice in the automotive industry these days.


The above robot control could be accomplished using PLC controllers (shown on the left) by writing very basic movement functions dependent on time.

Engineers representing programming logic in a very simple visual form is just the start to more complex processes. One major hurdle that every engineer tends to address is how to get the most out of the PLC/chip/microcontroller.

Here is a DW report on The power of algorithms and how a forecasting model is used by logistics companies to make better algorithms. The video also gives a glimpse into moral aspects of using algorithms to predict human behavior.

DW report on algorithms

Other literature:

Tesla releases new Autopilot 2.0 software update, adds Automatic High Beam worldwide

Why hardware-based security will always trump software


Ashwin Shreshta

Solar & automotive technology consultant

How highly-efficient well-planned solar technology can be a domino effect to energy success

As you know, renewable energy in India has seen a recent boom in the past 5-7 years, especially or primarily in the solar energy space. India aims to achieve a 100 Giga Watt (GW) of solar installations by 2022 with tariff rates dropping as we speak. More importantly, tariffs are already cheaper than conventional power tariffs.

Solar innovation:

Innovation in the solar sector can be split into 2 broad categories: Solar cell innovation and retrofit technology. Intellectual Property (IP) on solar cell material science belong to a select few companies, countries and institutes. This restriction has hence led to blossoming of cheaper, faster and more accessible forms of retrofit innovation like solar trackers, module-level MPPT (Maximum Power Point Tracking), automated cleaning, structural health monitoring and solar tiles just to name a few. In solar installations, Capex (Capital Expenditure) cost increases are related to the ‘extra’ devices retrofitted to the fundamental panel technology and faster return on investments are why they are considered in the first place.

With solar no longer being subsidised by the government like it used to, Capex cost increases are considerable enough and this has led to a preference of ‘non-risky’ simplistic solar installations in the country.

Better solar fields imply seamless energy transfer:

Innovation in solar is highly important because of the reliability issues associated with current solar technology. Even at 100 GW, India would still be producing only 9% of the total power consumption and this is considering that the sun shines consistently 300 days in a year. With solar power plants being spread out over acres, a shadow on one side of the plant will affect the power production overall or one could take the problem case of panels not facing the sun throughout the day which can reduce power production by as much as 14%.

The below image taken from German trade and Invest presentation of 2011 shows that the transition to conventional energy post5pm from solar is one of the major hurdles a solar energy reliant country will need to keep in mind.

How price drops affect innovation in the energy sector:

Renewable energy in India is still in its nascent stage and still requires significant government support if it is to even replace some part of the conventional grid. If we continue to drop unit prices just based on contracts, this will be a serious detriment to alternative forms of innovation.

Outline of some common problems:

·        Solar power has to compete with conventional energy generation.

·        Bidding contracts highly regulated with over-dependency on cheapest price of the bidder.

·        Indigenous innovation on solar technology still a rarity.

·        India imports most of its 99% pure silicon from China with an import duty of 25%.

An ideal situation:

In a decade time span, our cities would be supplied with power generated few 100kms away, most probably a solar power plant spread over acres. Once the natural resource of energy generation runs out, there will come a time when reliability of mass scale renewable power will be a major necessity. India would need to start to design for this future as soon as possible and give up on the existing mode of adopting this raw plug-and-play technology.

Most of these pockets of solar energy generation will soon drive the cities of our future.

The solution

An ideal solution would be to create a USP around the application of solar power generated that will make it irreplaceable by the conventional grid.

Case study

One example of great planning of renewable and more specifically solar installations is Portugal which in 2016 achieved 95.5% of its entire energy delivered by renewable energy.

In solar energy, Portugal split its installations with energy generation from 1. Solar PV and 2. Solar thermal depending on the installed location.

24 hours of energy provided by solar energy storage gets rid of the post5pm hassle of transitioning to coal-based energy.

I do hope this is useful to you.


Ashwin Shreshta

Solar & automotive technology consultant

Vaahan Renew Energy Pvt. Ltd.

Electric vehicle safety

Source: Electric vehicle safety

Electric vehicle safety


Frontal crash of an electric vehicle at 64 KPH

Vehicle safety used to be a back-end job, with engineers toiling in the crash lab analyzing, testing and validating different materials for their crash absorption characteristics. Now, it has become a sign of pride for most of the OEMs.

Differences in architecture between EVs and ICEs:

One might assume that electric vehicles would perform in a similar way to conventional ICEs (Internal Combusion Engine s) but this is not true. In comparison to ICEs , EVs (Electric Vehicles) have a different drive-train layout & the power source i.e. battery pack is very different to a conventional cylindrical fuel tank. Even the HVAC (Heating Ventilation And Cooling) system in modern EVs are taking a different shape and size. The only systems resembling ICEs seem to be the suspension systems for now but even this is beginning to skew towards a different technology Literature.


Modern vehicle body-in-white structures are no longer heavy and bulky built, instead ‘impact energy absorption’ has become a methodology for success. A normal crash test team goes about determining load-paths for a vehicle during crash in order to best divert forces away from the passenger compartment and for an EV, they also try and keep the forces away from the battery pack. Since Li-ion batteries have a state of instability which could lead to fires under high impact conditions or thermal runaway, safety of the battery pack is of high priority.

A load path and stress distribution chart are what crash engineers rely on.

Legal standards:

Crash legal requirements & consumer ratings are set by agencies such as Euro-ncap,Us-ncap, Japenese-ncap, Iihs etc. and they give a rating in terms of stars with 5 being the most safest. A technical evolution in these tests is that they rate the vehicles not just in terms of passive safety but also crash avoidance systems, high-voltage protection, post-crash safety and many more. Some examples of crash test standards are FMVSS 208, FMVSS 214, FMVSS 301, ECE R94, ECE R95, TRIAS 47 etc. How to read the stars NCAP

Comparison in safety:

Yes depending on the vehicle class and one can verify this with a number of studies Study on crashworthiness of electric. Moreover, the improvements in EV safety are happening at such a rapid pace, vehicle homologation agencies are not able to keep-up. Just as an example, the underbelly of EVs used to be a major concern during fast collisions with road-lying objects. This part of the vehicle has been improved so much more in terms of crash safety that software updates are sent to the raise the vehicle using its suspension system in rocky areas.

On a more economics note, there are different body structures that deliver better profits to the OEMs and this is a work under process, especially for electric vehicles. Volume sales, body architecture and profitability are crucial variables in vehicle safety for any vehicular platform.


Ashwin Shreshta

Solar & automotive technology consultant



Engineer’s design dilemma

It’s been almost a week of work at the workshop and the metal structures are finally taking shape. Along the way, I had spent many hours consulting with experienced mechanical engineers on whether the structure would hold the weight I wanted them to. It was mind-boggling the amount of data they had on their finger-tips. In addition to this, I spent countless hours drawing-up CAD models, performing FEM analysis and filling-up my notebook with stress calculations. Do I trust the theoretical calculations on paper or the empirical advice of an experienced engineer? Would they add-up in the end?

This is a problem most of the engineers face. Its cheap to buy a notebook, pen, a book and workout an engineering problem from a college dorm or an office or a home. What’s not cheap is building the full-sized contraption in a humid, dusty workshop and then testing if your assumptions were correct. Would India ease this transition from chalk-board to machine-shop for budding inventors? 

But the joy of working-out complex models on paper is incredible. Dr. Amar Bose had worked out the theory behind ‘noise-cancelling headphones’ on a flight between 2 cities. ‘Wearable device’ nevertheless, but extremely complex mathematics behind the electronics. I guess it did add-up in the end for Bose corp.










Strain energy, shape functions, minimum potential energy principle

New blog post: Relating the minimum potential energy principle to FEM.

Why systems of nature assume states with the lowest energies is a question that even automotive engineers have to contemplate with. The minimum potential energy principle is used in Finite Element structural Analysis. Read on further to learn about shape functions and the basic concepts in FEM.

Source: Strain energy, shape functions, minimum potential energy principle

Second order DEs in vehicle crash analysis

New blog on the mathematics of vehicle crash analysis and its connection to differential equations (DEs)
Second order DEs in vehicle crash analysis.

Second order DEs in vehicle crash analysis

The following excerpt I take from the impeccably written book ‘Differential Equations with applications and written notes’ by George F.Simmons.

‘The use of complex numbers in the mathematics of electric circuit problems was pioneered by the mathematician, inventor and electrical engineer Steinmetz. He was employed by General Electric Company and quickly became the greatest of electrical engineers. Steinmetz solved problems of mass production of electric motors using mathematics.One day, a huge new generator at Henry Ford’s River Rouge plant had gone Kaput. His electrical engineers were unable to locate the problem. In comes Steinmetz with a piece of chalk, few sheets of paper and starts scribbling down calculations while listening to the generator for 2 whole days….doesn’t change a single part in between. He descends finally, asking the engineers to take out 16 windings from the field coil. Generator works and Steinmetz submits a bill of $ 10,000. Ford respectfully asks for a itemized statement. Steimetz replies as follows: ” Making chalk mark on generator $1. Knowing where to make mark $9,999. Total due $10,000”. ‘ Haha…..


  • Second order differential equations (DEs).
  • Applications of second order DEs in vehicle crash and other fields.


Most engineers come across the second order differential equation during their undergraduate years. Some of the common 2nd order DEs'(Differential Equations)  in engineering  are the following below, often abbreviated under MSD (Mass Spring Damper) systems:

m\ddot{x}+c\dot{x}+kx=F(x)  – 1

L\ddot{I}+R\dot{I}+\frac{1}{C}I=\dot{E}   – 2

MSD-like systems in engineering occur in various fields, for example:

  1. Animal running (ref: Running springs: speed and animal size)
  2. RLC Circuits
  3. Robotics (PD control) and lastly,
  4. Automotive (Cruise Control, car suspension etc.)

Solving linear or non-linear homogeneous equations is actually kinda easy, once you memorize the formulas and the various forms in which they appear. Its more important to understand why most of the solutions are of the form of an exponential or a sine/cosine form. Its because the exponential or the sine/cosine maintain their function form on double differentiation (2nd order). So, in conclusion, the two main behaviors that one observes from the solutions of 2nd order differential equations are 1. Trigonometric 2. Exponential 3. Combination of the two. This is probably the single important insight I gained about 2nd order DEs during my Bachelor’s degree. Solutions of differential equations are usually split into two terms:

  1. Complementary function
  2. Particular integral.

The particular integral results from the forcing part and is the steady-state part of the solution. The complementary function shows the process by which the mass reaches the steady-state solution i.e it is the transient part of the solution. Transient response implies that this term of the solution dies-out as t\rightarrow \infty .

Lumped parameters-

When it comes to vehicle crash modeling and analysis, the analysis part is categorized into two broad categories, namely:

  1. Lumped parameter analysis
  2. Finite Element Analysis
(refer: Lumped parameter analysis-example case)

I can explain ‘lumped parameters’ by a simple example. If you remember some of those early classes from electrical circuits, you would remember the fact that almost all conducting wires used in circuits carry some electrical resistance with it. A circuit might utilize tens of thousands of wires and it would tough assigning a resistance for each and every wire. So instead, we group all the resistances from the wires and model it using a single ‘lumped parameter’ i.e. a single resistor in the circuit. This is the most common example, although lumped parameters are also used in crash analysis to reduce the computation time. Why that is the case, you can make-up your mind after reading the explanation in the below topic.

Creating a mathematical model for vehicle crash-

Second order differential equations are also used for modeling vehicle crash situations. This is possible by making a few assumptions, for example, considering the 2 vehicles crashing into each other as 2 rigid masses and their crumple zones as a system of springs and dampers. This can be visualized from the first diagram in the pic below. This model is called as the ‘Kelvin model’ of vehicle crash analysis. I will iterate again, lumped parameter analysis does seem like a gross generalization of reality, but its worth the effort after validation from real-world tests. This is because of the use of continuous DEs and hence way faster computing times. Image für Crashaufprall D.g           The solution here is comprised only of the transient response part as there is no forcing function. The main aim from the above Kelvin model is to determine the crumple zone stiffness, crumple zone damping and the natural frequency of vibration. After solving the DEs in Matlab, one can obtain the graph of the relative deceleration of the vehicle 1 (mass1) w.r.t mass 2. From this, the absolute deceleration of the 2 vehicles can be separately calculated.

Using parameters in DEs to quantify solutions:

The topic of validation is also relatively new to me. But, I can put down in writing a few things I learned here and there. Obviously, it makes no sense just to chalk-up a spring-mass-damper system and derive the analytical solutions and then graph it up. The next stage is to now associate the parameters of the second order DE described above with real world parameters. This part seems the hardest to me. Normally, we would attach a mass to a spring and a dashpot, attach an displacement transducer to the mass and hit it with a impulse hammer. The readings of the transducer are then plotted with a graph against time, zero disp. being the point of attachment. The set of discrete displacements are then used to calculate parameters such as ‘period of oscillation’, ‘damping ratio’, ‘angular frequency’ etc. A brief description of how the parameters are obtained can be seen from the Figure 3 (at the end).

real vs test

Vehicle crash validation method:

Vehicle crashes involve the displacement of the front-end (vehicle crush). Once the test data on the crash test is received, usually a force-displacement curve from the transducers, our next step is to setup parameters to match the graphical solutions of the second order DEs to the test curves. The forces during a crash are replaced by using pulses in our mathematical models. This can also be done by using a detailed FEM model of the crash vehicle and matching the intrusion to the test vehicle by varying the magnitudes of crash pulses.

Observe from the below figure the different stages of vehicle crash modeled from DEs. Look at the connections between maximum vehicle crush and velocity. Look at how the signage of the acceleration changes at the end of the restitution phase. These are parameters one can use to quantify the Kelvin model.

What do we infer from the graphical solution?  The magnitude of the maximum displacement of vehicle crush, maximum deceleration and the resp. times during the entire collision phase.


Figure 3: Parameters used to quantify the analytical solutions of a MSD system.


Cashless payment for vehicle crashes in India

Ford F150 gets mixed crash results

PoPP3- Pythagoras theorem [Ved1]

For Ved.

Hallo! Time for some math. Fundamentals of mathematics are very interesting. This is because of the way these ideas came to life. Take for example the ‘Pythagoras theorem’. When you look at it at first glance, you see only a formula. A formula made up of letters with the number 2 on top of each of them. But, the idea of the theorem is something more deep. Most of the basic mathematics that you will learn in school stems from calculations on a farming field. Pythagoras theorem is no exception. Look at these notes I’ve written below.

Pythagoras theorem originated as a relation between the areas of the squares on the triangle. Take any Pythagorean triple and you will observe this phenomenon of the areas. You could go out on a beach and try drawing squares such that you have a right-angled triangle forming on the inside. Measure the sides of the squares and calculate the areas by hand. You will see that the theorem holds true. But, what you did on the beach is an empirical proof. Theorems in mathematics are not empirical, rather they have a greater meaning. Its called deduction. I can’t explain it in words. You will have to feel it.

The proof of the pythagoras theorem I performed above is a geometrical proof. The proof stems from the fact that a square can be made by joining 2 right angled triangles together.

Far more powerful is the algebraic proof that I wrote above. Now comes the most important part of today’s lesson. Remember when I told you that the Pythagoras theorem started-off as a relation between the areas of the squares? The algebraic proof shows you that the Pythagoras theorem can also be used to define the length of a line between 2 points.

Pythaogoreans were a sect existing during the time of Greek mathematics. To put time into perspective, the Indus valley civilization existed some 2000 years Before Christ was born. The Babylonians also existed some 2000 B.C. Greek civilization was around 700 B.C. Pythagoras lived at around 500 B.C. When the Pythagoreans found that the length of the side opposite the right angle(with 1 and 1 as its shorter sides) cannot be measured accurately, they did some horrible things. Thus, began a new puzzle in mathematics called the Irrational numbers.


How do you prove that a number is irrational?


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