The use of lithium titanate Oxide (LTO) batteries with supercapacitors in micro- and mild hybrid vehicles has been studied. The study involves vehicle simulations and laboratory tests of carbon/carbon supercapacitors and 20Ah LTO cells from EIG, Korea. Cycle testing of the LTO cells/module on a cycle to simulate their use with supercapacitors indicated that their charge acceptance was excellent even at a charging power of 2000W (500W/cell). The test data indicated that the LTO battery would be an excellent choice for micro-hybrid applications. Simulations of micro- and mild hybrid vehicle operation have been run using lead-acid and EIG LTO battery technologies in 16V and 48V system. It is clear from the results that the LTO batteries can function well in both the micro- and mild hybrids. The LTO batteries are much smaller than the lead-acid batteries and are more efficient. The LTO batteries had an efficiency of 95-97% while the lead-acid batteries had an efficiency of 85-88%. The effect on fuel economy of the higher efficiency of the LTO batteries was not significant for either the FUDS or highway driving cycle. This was true for even the accessory load of 800W.

Background

Single Nucleotide Polymorphism (SNP) analysis only captures a small proportion of associated genetic variants in Genome-Wide Association Studies (GWAS) partly due to small marginal effects. Pathway level analysis incorporating prior biological information offers another way to analyze GWAS's of complex diseases, and promises to reveal the mechanisms leading to complex diseases. Biologically defined pathways are typically comprised of numerous genes. If only a subset of genes in the pathways is associated with disease then a joint analysis including all individual genes would result in a loss of power. To address this issue, we propose a pathway-based method that allows us to test for joint effects by using a pre-selected gene subset. In the proposed approach, each gene is considered as the basic unit, which reduces the number of genetic variants considered and hence reduces the degrees of freedom in the joint analysis. The proposed approach also can be used to investigate the joint effect of several genes in a candidate gene study.

Results

We applied this new method to a published GWAS of psoriasis and identified 6 biologically plausible pathways, after adjustment for multiple testing. The pathways identified in our analysis overlap with those reported in previous studies. Further, using simulations across a range of gene numbers and effect sizes, we demonstrate that the proposed approach enjoys higher power than several other approaches to detect associated pathways.

Conclusions

The proposed method could increase the power to discover susceptibility pathways and to identify associated genes using GWAS. In our analysis of genome-wide psoriasis data, we have identified a number of relevant pathways for psoriasis.