...

• The loop specifics sub-project is basically a simulation of the loop (think of something like an analytical way of solving a differential equationnumerical analysis, but optimizing/using our model instead of a some differential equation, we use our model)

• The binary decision sub-project requires data from the loop + external data. This makes this sub-project dependent on the loop specifics sub-project

...

This means we have 5 types of data that we have to consider:

• Input data: Data that we have when at the “start” of the segment. This includes things like initial velocity, initial battery charge

• Segment data: This is constant data about the segment itself. This includes the elevation gain, speed limit, expected charge from solar panels, etc. This data is constant for the segment itself, but may not be constant for the route (since a route is composed of many segments). For example, the segment will always have the same weather conditions but this is not true for the route weather conditions. Using a programming analogy, this is basically a local constant

• Route data: This is constant data about the route. This data will not change for the route and each segment “inherits” this data. Using a programming analogy, this is basically a global constant

• Variable data: These are the variables that we want to optimize (or calculate for) using some model. Types of variable data that we would want to optimize for include minimal/minimum energy use, maximal/maximum velocity, etc.

• Output data: This data is calculated using our variable data. This includes things like final velocity, final battery charge, etc. This output data would be the new input data for the next segment

The design of the algorithm somewhat mimics the idea of a numerical analysis algorithm where we have some input, use that input to calculate the output, then use that output as the input at the next “step”. Instead of “steps”, we have segments. And a route is made of many of these segments. The algorithm design is as follows:

1. Get all input, segment, and route data for our current segment

2. Using that data, determine the values of our variable data (this is the optimizing step)

   • Option 1: Optimize for a variable (ie. max velocity) and determine what values our other variable data need to be such that our optimizing variable is optimized (easier method)

   • Option 2: Multivariable optimization such that all our variable data values are optimized → Some variable data may be dependent on each other (hard method, will need to come up with an optimization model)

3. Calculate output data using our optimized variable data

4. Use output data as the input data for the next segment and repeat this algorithm on that segment

Inputs/Factors

Outputs

Notes

https://www.reddit.com/r/askscience/comments/rmwih/can_you_help_explain_this_mythbusters_result/

https://www.reddit.com/r/askscience/comments/o5dfo/when_driving_on_a_downhill_slope_followed/

https://www.reddit.com/r/askscience/comments/19ql3r/which_uses_less_energy_accelerating_down_a_hill/