BUG: dtype ignored in pd.read_excel
I'm trying to read an excel file with pd.read_excel(). 
The excel file has 2 columns Date and Time and I want to read both columns as str not the excel dtype.


Example of the excel file
[test1.xlsx](https://github.com/pandas-dev/pandas/files/6006593/test1.xlsx)


When using the dtype or the converters arguments the dtype of the columns remain the same

```
df = pd.read_excel('xls_test.xlsx',
                   dtype={'Date':str,'Time':str})
df.dtypes
Date    object
Time    object
dtype: object
```
```
df.head()
Date	Time
0	2020-03-08 00:00:00	10:00:00
1	2020-03-09 00:00:00	11:00:00
2	2020-03-10 00:00:00	12:00:00
3	2020-03-11 00:00:00	13:00:00
4	2020-03-12 00:00:00	14:00:00

```

Same thing when using converters

```
df = pd.read_excel('xls_test.xlsx',
                   converters={'Date':str,'Time':str})
df.dtypes
Date    object
Time    object
dtype: object
```
```
df.head()
Date	Time
0	2020-03-08 00:00:00	10:00:00
1	2020-03-09 00:00:00	11:00:00
2	2020-03-10 00:00:00	12:00:00
3	2020-03-11 00:00:00	13:00:00
4	2020-03-12 00:00:00	14:00:00

```

I have also tried to use other engine but the result is always the same.


### pd.show_versions()

```
INSTALLED VERSIONS
------------------
commit           : 7d32926db8f7541c356066dcadabf854487738de
python           : 3.8.5.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.2.0
Version          : Darwin Kernel Version 20.2.0: Wed Dec  2 20:39:59 PST 2020; root:xnu-7195.60.75~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_AU.UTF-8
LOCALE           : en_AU.UTF-8

pandas           : 1.2.2
numpy            : 1.20.1
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 50.3.1.post20201107
Cython           : 0.29.21
pytest           : 6.1.1
hypothesis       : None
sphinx           : 3.2.1
blosc            : None
feather          : None
xlsxwriter       : 1.3.7
lxml.etree       : 4.6.1
html5lib         : 1.1
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.19.0
pandas_datareader: None
bs4              : 4.9.3
bottleneck       : 1.3.2
fsspec           : 0.8.3
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.2
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.6
pandas_gbq       : None
pyarrow          : None
pyxlsb           : 1.0.8
s3fs             : None
scipy            : 1.5.2
sqlalchemy       : 1.3.20
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : 1.3.0
numba            : 0.52.0
```

This seems too obvious to be an unreported bug and I apologise if the problem comes from my side.