Role of electrical resistance of electrodes in modeling of discharging and charging of flooded lead-acid batteries

Electrical resistance of both the electrodes of a lead-acid battery increases during discharge due to formation of lead sulfate, an insulator. Work of Metzendorf 1] shows that resistance increases sharply at about 65% conversion of active materials, and battery stops discharging once this critical conversion is reached. However, these aspects are not incorporated into existing mathematical models. Present work uses the results of Metzendorf 1], and develops a model that includes the effect of variable resistance. Further, it uses a reasonable expression to account for the decrease in active area during discharge instead of the empirical equations of previous work. The model's predictions are compared with observations of Cugnet et al. 2]. The model is as successful as the non-mechanistic models existing in literature. Inclusion of variation in resistance of electrodes in the model is important if one of the electrodes is a limiting reactant. If active materials are stoichiometrically balanced, resistance of electrodes can be very large at the end of discharge but has only a minor effect on charging of batteries. The model points to the significance of electrical conductivity of electrodes in the charging of deep discharged batteries. (C) 2014 Elsevier B.V. All rights reserved.

Simulation of Effective Thermal Conductivity of Metal Hydride Packed Beds

Several mathematical models are available for estimation of effective thermal conductivity of nonreactive packed beds. Keeping in view the salient differences between metal hydride beds in which chemisorption of hydrogen takes place and conventional nonreactive packed beds, modified models are proposed here to predict the effective thermal conductivity. Variation in properties such as solid thermal conductivity and porosity during hydrogen absorption and desorption processes are incorporated. These extended models have been applied to simulate the effective thermal conductivity of the MmNi(4.5)Al(0.5) hydride bed and are compared with the experimental results. Applicability of the extended models for estimation of the effective thermal conductivity at different operating conditions such as pressure, temperature, and hydrogen concentration is discussed.