The performance of lithium-ion battery energy storage system (BESS) declines sharply at low temperatures

making it difficult to meet the power demand of high-power pulse loads (HPPL). Therefore

this paper proposes a multi-objective joint optimization method for capacity allocation and low-temperature preheating strategies of a passive lithium-ion battery-supercapacitor hybrid energy storage system (HESS)

aiming to solve the power supply issue of HPPL at low temperatures. Firstly

an electro-thermal-aging coupling model is established to describe the dynamic characteristics of the passive HESS at low temperatures. Then

a joint optimization model

aiming to minimize the mass and the minimum operating temperature of the HESS

is solved by the non-dominated sorting genetic algorithm with elitist strategy. Finally

a case study is conducted. The results show that the joint optimization schemes for the HESS at low temperatures perform significantly better than the BESS schemes in terms of the system mass and acquisition cost

as the system mass of the former is 44.18% lower at −40 ℃. The HESS schemes require less single pulse cost and preheating time than the BESS schemes across the entire temperature range; the average single pulse cost of the former is only 52.50% of the latter

and the average preheating time of the former is only 35.63% of the latter.