lme4: How to specify random slopes while constraining all correlations to 0?

Question

Due to an interesting turn of events, I'm trying use the lme4 package in R to fit a model in which the random slopes are not allowed to correlate with each other or the random intercept. Effectively, I want to estimate the variance parameter for each random slope, but none of the correlations/covariances. From the reading I've done so far, I think what I want is effectively a diagonal variance/covariance structure for the random effects.

An answer to a similar question here provides a workaround to specify a model where slopes are correlated with intercepts, but not with each other. I also know the || syntax in lme4 makes slopes that are correlated with each other, but not with the intercepts. Neither of these seems to fully accomplish what I'm looking to do.

Borrowing the example from the earlier post, if my model is:

m1 <- lmer (Y ~ A + B + (1+A+B|Subject), data=mydata)

is there a way to specify the model such that I estimate variance parameters for A and B while constraining all three correlations to 0? I would like to achieve a result that looks something like this:

VarCorr(m1)    
##  Groups   Name        Std.Dev. Corr       
##  Subject  (Intercept) 1.41450             
##           A           1.49374  0.000      
##           B           2.47895  0.000 0.000
##  Residual             0.96617    

I'd prefer a solution that could achieve this for an arbitrary number of random slopes. For example, if I were to add a random effect for a third variable C, there would be 6 correlation parameters to fix at 0 rather than 3. However, anything that could get me started in the right direction would be extremely helpful.

Edit:

On asking this question, I misunderstood what the || syntax does in lme4. Struck through the incorrect statement above to avoid misleading anyone in the future.