diff --git a/doc/source/whatsnew/v0.23.0.txt b/doc/source/whatsnew/v0.23.0.txt
index 65e0062fea0cb..783de6569a542 100644
--- a/doc/source/whatsnew/v0.23.0.txt
+++ b/doc/source/whatsnew/v0.23.0.txt
@@ -378,7 +378,7 @@ Conversion
 - Fixed bug where comparing :class:`DatetimeIndex` failed to raise ``TypeError`` when attempting to compare timezone-aware and timezone-naive datetimelike objects (:issue:`18162`)
 - Bug in :class:`DatetimeIndex` where the repr was not showing high-precision time values at the end of a day (e.g., 23:59:59.999999999) (:issue:`19030`)
 - Bug where dividing a scalar timedelta-like object with :class:`TimedeltaIndex` performed the reciprocal operation (:issue:`19125`)
-- Bug in ``IntervalDtype`` when constructing two instances with subtype ``CategoricalDtype`` where the second instance used cached attributes from the first (:issue:`18980`)
+-
 
 Indexing
 ^^^^^^^^
diff --git a/pandas/core/dtypes/dtypes.py b/pandas/core/dtypes/dtypes.py
index fce371bec363d..2ec35889d6a7a 100644
--- a/pandas/core/dtypes/dtypes.py
+++ b/pandas/core/dtypes/dtypes.py
@@ -654,7 +654,7 @@ def __new__(cls, subtype=None):
             u.subtype = None
             return u
         elif (isinstance(subtype, compat.string_types) and
-              subtype in ('interval', 'interval[]')):
+              subtype.lower() == 'interval'):
             subtype = None
         else:
             if isinstance(subtype, compat.string_types):
@@ -667,11 +667,6 @@ def __new__(cls, subtype=None):
             except TypeError:
                 raise ValueError("could not construct IntervalDtype")
 
-        if subtype is None:
-            u = object.__new__(cls)
-            u.subtype = None
-            return u
-
         if is_categorical_dtype(subtype) or is_string_dtype(subtype):
             # GH 19016
             msg = ('category, object, and string subtypes are not supported '
@@ -679,15 +674,11 @@ def __new__(cls, subtype=None):
             raise TypeError(msg)
 
         try:
-            # GH 18980: need to combine since str and hash individually may not
-            # be unique, e.g. str(CategoricalDtype) always returns 'category',
-            # and hash(np.dtype('<m8')) == hash(np.dtype('<m8[ns]'))
-            key = ''.join([str(subtype), str(hash(subtype))])
-            return cls._cache[key]
+            return cls._cache[str(subtype)]
         except KeyError:
             u = object.__new__(cls)
             u.subtype = subtype
-            cls._cache[key] = u
+            cls._cache[str(subtype)] = u
             return u
 
     @classmethod
@@ -712,7 +703,7 @@ def __hash__(self):
 
     def __eq__(self, other):
         if isinstance(other, compat.string_types):
-            return other.title() in (self.name.title(), str(self).title())
+            return other.lower() in (self.name.lower(), str(self).lower())
         elif not isinstance(other, IntervalDtype):
             return False
         elif self.subtype is None or other.subtype is None:
diff --git a/pandas/tests/dtypes/test_dtypes.py b/pandas/tests/dtypes/test_dtypes.py
index b3faffb159795..692fb3271cfda 100644
--- a/pandas/tests/dtypes/test_dtypes.py
+++ b/pandas/tests/dtypes/test_dtypes.py
@@ -458,7 +458,7 @@ def test_construction(self, subtype):
         assert i.subtype == np.dtype('int64')
         assert is_interval_dtype(i)
 
-    @pytest.mark.parametrize('subtype', [None, 'interval', 'interval[]'])
+    @pytest.mark.parametrize('subtype', [None, 'interval', 'Interval'])
     def test_construction_generic(self, subtype):
         # generic
         i = IntervalDtype(subtype)
@@ -535,8 +535,8 @@ def test_equality(self):
                                   IntervalDtype('float64'))
 
     @pytest.mark.parametrize('subtype', [
-        None, 'interval', 'interval[]', 'int64', 'uint64', 'float64', object,
-        CategoricalDtype(), 'datetime64', 'timedelta64', PeriodDtype('Q')])
+        None, 'interval', 'Interval', 'int64', 'uint64', 'float64',
+        'complex128', 'datetime64', 'timedelta64', PeriodDtype('Q')])
     def test_equality_generic(self, subtype):
         # GH 18980
         dtype = IntervalDtype(subtype)
@@ -544,8 +544,8 @@ def test_equality_generic(self, subtype):
         assert is_dtype_equal(dtype, IntervalDtype())
 
     @pytest.mark.parametrize('subtype', [
-        'int64', 'uint64', 'float64', 'complex128', np.dtype('O'),
-        CategoricalDtype(), 'datetime64', 'timedelta64', PeriodDtype('Q')])
+        'int64', 'uint64', 'float64', 'complex128', 'datetime64',
+        'timedelta64', PeriodDtype('Q')])
     def test_name_repr(self, subtype):
         # GH 18980
         dtype = IntervalDtype(subtype)
@@ -553,7 +553,7 @@ def test_name_repr(self, subtype):
         assert str(dtype) == expected
         assert dtype.name == 'interval'
 
-    @pytest.mark.parametrize('subtype', [None, 'interval', 'interval[]'])
+    @pytest.mark.parametrize('subtype', [None, 'interval', 'Interval'])
     def test_name_repr_generic(self, subtype):
         # GH 18980
         dtype = IntervalDtype(subtype)
@@ -600,15 +600,6 @@ def test_caching(self):
         tm.round_trip_pickle(dtype)
         assert len(IntervalDtype._cache) == 0
 
-    def test_caching_categoricaldtype(self):
-        # GH 18980
-        cdt1 = CategoricalDtype(list('abc'), True)
-        cdt2 = CategoricalDtype(list('wxyz'), False)
-        idt1 = IntervalDtype(cdt1)
-        idt2 = IntervalDtype(cdt2)
-        assert idt1.subtype is cdt1
-        assert idt2.subtype is cdt2
-
 
 class TestCategoricalDtypeParametrized(object):