Here is the situation:
I have a table value function with a datetime parameter ,lest's say tdf(p_date) , that filters about two million rows selecting those with column date smaller than p_date and computes some aggregate values on other columns.
It works great but if p_date is a custom scalar value function (returning the end of day in my case) the execution plan is altered an the query goes from 1 sec to 1 minute execution time.

A proof of concept table - 1K products, 2M rows:

CREATE TABLE [dbo].[POC](
    [Date] [datetime] NOT NULL,
    [idProduct] [int] NOT NULL,
    [Quantity] [int] NOT NULL
) ON [PRIMARY]

The inline table value function:

CREATE FUNCTION tdf (@p_date datetime)
RETURNS TABLE 
AS
RETURN 
(
    SELECT idProduct, SUM(Quantity) AS TotalQuantity,
         max(Date) as LastDate
    FROM POC
    WHERE (Date < @p_date)
    GROUP BY idProduct
)

The scalar value function:

CREATE FUNCTION [dbo].[EndOfDay] (@date datetime)
RETURNS datetime
AS
BEGIN
    DECLARE @res datetime
    SET @res=dateadd(second, -1,
         dateadd(day, 1, 
             dateadd(ms, -datepart(ms, @date),
                 dateadd(ss, -datepart(ss, @date),
                    dateadd(mi,- datepart(mi,@date),
                         dateadd(hh, -datepart(hh, @date), @date))))))
    RETURN @res
END

Query 1 - Working great

SELECT * FROM [dbo].[tdf] (getdate())

The end of execution plan: Stream Aggregate Cost 13% <--- Clustered Index Scan Cost 86%

Query 2 - Not so great

SELECT * FROM [dbo].[tdf] (dbo.EndOfDay(getdate()))

The end of execution plan: Stream Aggregate Cost 4% <--- Filter Cost 12% <--- Clustered Index Scan Cost 86%