1. Open the model.

open_system('sldemo_househeat');

2. Define a set of values for different temperatures.

setPointValues = 65:2:85;
spv_Length = length(setPointValues);

3. Using setPointValues, initialize an array of Simulink.SimulationInput objects.

in(1:spv_Length) = Simulink.SimulationInput('sldemo_househeat');
for i = 1:1:spv_Length 
    in(i) = in(i).setBlockParameter('sldemo_househeat/Set Point',...
        'Value',num2str(setPointValues(i)));
end

4. Specify the pool size of the number of workers to use. In addition to the number of workers used to run simulations in parallel, a head worker is required. In this case, assume that three workers are available to run a batch job for the parallel simulations. The job object returns useful metadata as shown. You can use the job ID to access the job object later from any machine. NumWorkers displays how many workers are running the simulations – the number of workers specified in the 'Pool' argument plus an additional head worker.

simJob = batchsim(in,'Pool',3)

                  ID: 1
                Type: pool
          NumWorkers: 4
            Username: #####
               State: running
      SubmitDateTime: ##-###-#### ##:##:##
       StartDateTime: 
    Running Duration: 0 days 0h 0m 0s

5. Access the results of the batch job using the fetchOutputs method. fetchOutputs returns an array of Simulink.SimulationOuput objects. You can fetch outputs only once simJob is in finished state.

out = fetchOutputs(simJob)

1x11 Simulink.SimulationOutput array