### Apache Airflow version

2.2.2 (latest released)

### Operating System

Ubuntu 18.04.6

### Versions of Apache Airflow Providers

_No response_

### Deployment

Other Docker-based deployment

### Deployment details

_No response_

### What happened

The deprecated variable `execution_date` raises an error when used in an f string template with date string formatting.

```python
In [1]: execution_date
DeprecationWarning: Accessing 'execution_date' from the template is deprecated and will be removed in a future version. Please use 'logical_date' or 'data_interval_start' instead.
Out[1]: <Proxy at 0x7fb6f9af81c0 wrapping DateTime(2021, 11, 18, 0, 0, 0, tzinfo=Timezone('UTC')) at 0x7fb6f9aeff90 with factory <function TaskInstance.get_template_context.<locals>.deprecated_proxy.<locals>.deprecated_func at 0x7fb6f98699d0>>

In [2]: f"{execution_date:%Y-%m-%d}"
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
----> 1 f"{execution_date:%Y-%m-%d}"

TypeError: unsupported format string passed to Proxy.__format__
```



### What you expected to happen

Executing `f"{execution_date:%Y-%m-%d}"` should return a string and not raise an error. 

### How to reproduce

```python
from datetime import datetime
from airflow import DAG
from airflow.operators.python import PythonOperator


def test_str_fmt(execution_date: datetime):
    return f"{execution_date:%Y-%m-%d}"


dag = DAG(
    dag_id="Test_Date_String",
    schedule_interval="@daily",
    catchup=False,
    default_args={
        "depends_on_past": False,
        "start_date": datetime(2021, 11, 1),
        "email": None,
        "email_on_failure": False,
        "email_on_retry": False,
        "retries": 0,
    },
)

with dag:
    test_task = PythonOperator(
        task_id="test_task",
        python_callable=test_str_fmt,
    )
```

### Anything else


```python
from datetime import datetime
...
datetime.fromisoformat(next_ds)
TypeError: fromisoformat: argument must be str
```


### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/models/taskinstance.py
:type run_id: datetime
        :param mark_success: Whether to mark the task as successful
        :type mark_success: bool
        :param ignore_all_deps: Ignore all ignorable dependencies.
            Overrides the other ignore_* parameters.
        :type ignore_all_deps: bool
        :param ignore_depends_on_past: Ignore depends_on_past parameter of DAGs
            (e.g. for Backfills)
        :type ignore_depends_on_past: bool
        :param ignore_task_deps: Ignore task-specific dependencies such as depends_on_past
            and trigger rule
        :type ignore_task_deps: bool
        :param ignore_ti_state: Ignore the task instance's previous failure/success
        :type ignore_ti_state: bool
        :param local: Whether to run the task locally
        :type local: bool
        :param pickle_id: If the DAG was serialized to the DB, the ID
            associated with the pickled DAG
        :type pickle_id: Optional[int]
        :param file_path: path to the file containing the DAG definition
        :type file_path: Optional[str]
        :param raw: raw mode (needs more details)
        :type raw: Optional[bool]
        :param job_id: job ID (needs more details)
        :type job_id: Optional[int]
        :param pool: the Airflow pool that the task should run in
        :type pool: Optional[str]
        :param cfg_path: the Path to the configuration file
        :type cfg_path: Optional[str]
        :return: shell command that can be used to run the task instance