predicting speed time for normal car from 0 to 35mph

with the first tab in this excel file Car data which is a OBD2 Data read out I have to use this data to make a model that should be based on accelerating from rest to 35 mph and braking from 35 mph to rest. Your model needs to be able to predict the following things:

1. 0 to a given speed time (Example 0 – 35 mph time)
2. Braking time from any given speed.
3. Engine RPM vs speed for different gears.
4. How much gas your car uses for a given course.
5. A model of power vs speed for your vehicle.

Below is my code so far but I am honestly lost on where to go next...? I would think that using the interp1() function would be my best bet but i have not figured out a way to make the data come together with that method??? any guidance will be greatly appreciated!!

[~,sheet_name2] = xlsfinfo('OBD2 Data.xlsx');
for j = 1:numel(sheet_name2)
  data2{j} = xlsread('OBD2 Data.xlsx',sheet_name2{j});
end;
% figure(3)
% plot(data2{1,1})
% figure(4)
% plot(data2{1,2})
% figure(5)
% plot(data2{1,3})
% figure(6)
% plot(data2{1,4})
% figure(7)
% plot(data2{1,5})
% figure(8)
% plot(data2{1,6})

%% 0 to a given speed time (Example 0 – 35 mph time)

Time = data2{1}(:,1);
Acceleration01 = data2{1}(:,2);
Acceleration02 = data2{1}(:,3);
Acceleration03 = data2{1}(:,4);
Velocity01 = Acceleration01.*Time;% V = a * t m/s
Velocity02 = Acceleration02.*Time;% V = a * t m/s
Velocity03 = Acceleration03.*Time;% V = a * t m/s
Velocity035 = [Velocity01 Velocity02 Velocity03];
figure(9)
plot(Time,Velocity035);
x = Time;
y1 = Velocity01;
Z = polyfit(y1,x,35)
figure(10)
plot(Z)