Electric vehicle predictive thermal control

1 . A system comprising:

one or more processors configured to:

a) divide all roads within a predefined distance from a starting point into segments, for a plurality of consecutive predefined distances from a starting point;

b) determine a likelihood of travel, of a vehicle, along at least one path of segments leading to each road segment within each predefined distance of the plurality of consecutive predefined distances;

c) determine a projected battery demand of a battery of the vehicle for travel to each segment along each at least one path within each predefined distance, based on a respective likelihood of travel for each road segment within each respective distance;

d) determine a projected battery heat generation for the travel to each segment along each at least one path within each predefined distance, based on a respective projected battery demand for each road segment within each respective distance, in terms of heat generated over projected travel time projected to be used for the travel to each segment, wherein the projected battery heat generation is determined using at least one thermal model of the battery representing thermal dynamics of the battery under projected battery usage on each segment;

e) determine, for a plurality of consecutive time intervals, maximum accumulated projected heat generation, using the thermal model of the battery, for travel during each of the time intervals and a resultant maximum battery temperature, from aggregate heat generated based on the projected heat generation of each segment projected to be traveled;

f) determine, for at least each time interval wherein the maximum battery temperature exceeds a predefined threshold, battery cooling required to keep the battery temperature below the predefined threshold;

g) determine, for each time interval wherein required battery cooling exceeds a predefined maximum cooling capacity, excess cooling required to prevent the battery temperature exceeding the specified temperature threshold;

h) determine, for each time interval wherein required battery cooling is below a predefined maximum cooling capacity, the excess cooling available within the given time interval;

i) for a last time interval of the time intervals during which there is determined excess required cooling, schedule cooling, using determined excess achievable cooling of one or more time periods prior to the last time interval during which there is determined excess required cooling;

j) determine remaining maximum excess achievable cooling for all time intervals prior to the last time interval of the time intervals during which there is determined excess required cooling, in light of projected maximum accumulated heat generation combined with any additionally scheduled cooling for all time intervals prior to the last time interval of the time intervals during which there is determined excess required cooling; and

k) repeat steps i) and j) until at least one of either:

all excess required cooling of each respective time interval requiring excess cooling is accounted for by excess achievable cooling of prior time interval having excess achievable cooling; or

all excess achievable cooling is accounted for based on scheduled cooling.

2 . The system of claim 1 , wherein the maximum accumulated heat generation is maximum accumulated heat generation with at least a threshold likelihood of occurrence based at least in part on a predefined threshold likelihood compared to a likelihood the vehicle will travel each at least one path during each of the time intervals.

3 . The system of claim 1 , wherein the heat generation is initially determined in terms of distance and is converted into the time domain.

4 . The system of claim 1 , wherein the one or more processors are further configured to determine the likelihood of travel, of the vehicle, along all paths of segments leading to each road segment.

5 . The system of claim 1 , wherein the likelihood of travel time for a given distance is determined as a first probability distribution function.

6 . The system of claim 5 , wherein the projected battery demand is determined as a second probability distribution function, reflecting probable battery usage for each at least one path of segments.

7 . The system of claim 6 , wherein the projected heat generation is determined as a third probability distribution function, reflecting probable heat generation for each at least one path of segments based on the probably battery usage and a thermal model of the battery of the vehicle.

8 . The system of claim 7 , wherein the third probability distribution function is represented in the distance domain and is converted into the time domain to reflect probably heat generation over time.

9 . The system of claim 1 , wherein the excess cooling is further scheduled by moving consecutively backwards through the time intervals to schedule the cooling until the excess required cooling for the last time period is accommodated by an equal amount of precooling scheduled by the scheduled cooling over one or more prior time periods, by utilizing the excess achievable cooling of time intervals closer in time to the last time interval of the time intervals during which there is determined excess required cooling before using excess achievable cooling of time intervals further in time from the last time interval of the time intervals during which there is determined excess required cooling.