diff --git a/fluids/pump.py b/fluids/pump.py
index 530c94d7..9ce1f28a 100644
--- a/fluids/pump.py
+++ b/fluids/pump.py
@@ -375,6 +375,10 @@ def CSA_motor_efficiency(P: float, closed: bool=False, poles: int=2, high_effici
     Several low-efficiency standard high power values were added to allow for
     easy programming; values are the last listed efficiency in the table.
 
+    The high-efficiency standard covers 2, 4, and 6 pole motors only; the
+    minimum efficiency standard additionally covers 8 pole motors. A
+    ValueError is raised for unsupported pole counts.
+
     Examples
     --------
     >>> CSA_motor_efficiency(100*hp)
@@ -388,6 +392,11 @@ def CSA_motor_efficiency(P: float, closed: bool=False, poles: int=2, high_effici
        375 kW). As modified 2015-12-17.
        https://natural-resources.canada.ca/energy-efficiency/energy-efficiency-regulations/electric-motors-1-500-hp0746-375-kw
     """
+    if high_efficiency:
+        if poles not in (2, 4, 6):
+            raise ValueError("Only 2, 4, and 6 pole motors have high-efficiency standard values")
+    elif poles not in (2, 4, 6, 8):
+        raise ValueError("Only 2, 4, 6, and 8 pole motors have standard efficiency values")
     P = P/hp
     # This could be replaced by a dict and a jump list
     if high_efficiency:
diff --git a/tests/test_pump.py b/tests/test_pump.py
index cac96029..7583fa18 100644
--- a/tests/test_pump.py
+++ b/tests/test_pump.py
@@ -92,6 +92,11 @@ def test_CSA_motor_efficiency():
     nema_min_Ps = [0.755, 0.825, 0.84, 0.855, 0.855, 0.875, 0.875, 0.885, 0.895, 0.902, 0.902, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.945, 0.945, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.954, 0.954, 0.825, 0.84, 0.84, 0.875, 0.875, 0.875, 0.875, 0.895, 0.895, 0.91, 0.91, 0.924, 0.924, 0.93, 0.93, 0.936, 0.941, 0.945, 0.945, 0.95, 0.95, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.958, 0.8, 0.855, 0.865, 0.875, 0.875, 0.875, 0.875, 0.895, 0.895, 0.902, 0.902, 0.917, 0.917, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.74, 0.77, 0.825, 0.84, 0.84, 0.855, 0.855, 0.855, 0.885, 0.885, 0.895, 0.895, 0.91, 0.91, 0.917, 0.917, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.945, 0.945, 0.945, 0.945, 0.945, 0.945, 0.755, 0.825, 0.84, 0.84, 0.84, 0.855, 0.855, 0.875, 0.885, 0.895, 0.902, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.93, 0.936, 0.936, 0.945, 0.945, 0.945, 0.95, 0.95, 0.954, 0.958, 0.958, 0.825, 0.84, 0.84, 0.865, 0.865, 0.875, 0.875, 0.885, 0.895, 0.91, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.941, 0.941, 0.945, 0.95, 0.95, 0.95, 0.954, 0.954, 0.954, 0.954, 0.958, 0.958, 0.8, 0.84, 0.855, 0.865, 0.865, 0.875, 0.875, 0.885, 0.902, 0.902, 0.91, 0.917, 0.924, 0.93, 0.93, 0.936, 0.936, 0.941, 0.941, 0.945, 0.945, 0.945, 0.954, 0.954, 0.954, 0.954, 0.954, 0.954, 0.74, 0.755, 0.855, 0.865, 0.865, 0.875, 0.875, 0.885, 0.895, 0.895, 0.902, 0.902, 0.91, 0.91, 0.917, 0.924, 0.936, 0.936, 0.936, 0.936, 0.936, 0.936, 0.945, 0.945, 0.945, 0.945, 0.945, 0.945]
     assert_close1d(nema_min_P_calcs, nema_min_Ps)
 
+    with pytest.raises(Exception):
+        CSA_motor_efficiency(100*hp, poles=8, high_efficiency=True)
+    with pytest.raises(Exception):
+        CSA_motor_efficiency(100*hp, poles=3)
+
 def test_motor_efficiency_underloaded():
     full_efficiencies = [motor_efficiency_underloaded(P*hp,  .99) for P in (0.5, 2.5, 7, 12, 42, 90)]
     assert_close1d(full_efficiencies, [1, 1, 1, 1, 1, 1])