No abstract

Thermoelectric generators are efficient devices to recover energy from the automotive exhaust gas. In this paper, conversion efficiency of automotive thermoelectric generator (ATEG) and the maximum electrical power generated by the ATEG, defining as the power output of the ATEG excluding the energy loss caused to the engine improved by optimizing the number of thermoelectric modules (TEMs) and its distribution pattern in an ATEG. An advanced numerical model of ATEG considering the effect of the heat transfer among the adjacent TEMs' rows is developed with Simulation-X software. In order to acquire the ATEG's optimal electrical performance, a 3-step optimization is applied. First, 17 independent factors (the number of TEMs in each row from 1 to 18) are assessed and the significant parameters are screened using Plackett-Burman design. Second, an experiment designed with a central composite design is performed to analyze the sensitivity of six selected factors and a surrogate model is built through response surface method. Then, conflicts in two objectives are settled with a multi-objective genetic algorithm. According to the optimization results of a given ATEG, the maximum electrical power generated by the ATEG is 139.47 W and the conversion efficiency is 2.51% under steady engine condition. Finally, the performances of the optimized design under different engine conditions are discussed. The results show that the maximum power generated by the ATEG and efficiency respectively increase by 49.8% and 106.5% after optimization when the exhaust inlet temperature is 805 K and the mass flow rate is 0.5 kg/s. INDEX TERMS Automotive thermoelectric generator, multi-objective genetic algorithm, response surface method, thermoelectric modules, 3-step optimization. The associate editor coordinating the review of this manuscript and approving it for publication was Yan-Jun Liu. light weight, and non-mechanical vibration [2], [3]. In recent years, the TEG-based waste heat recovery method has been one of the most promising techniques [4]-[6]. Automotive thermoelectric generators (ATEGs) are proved to have the potential for recovering waste heat energy from automotive exhaust gas [7], [8]. For an internal combustion engine vehicle, approximately 30% of the energy is used to drive the vehicle; nevertheless, 40% is emitted as heat through the exhaust gas [9]-[11]. A variety of numerical TEG models have been developed for the parametric studies on the performance and optimization of ATEG. Espinosa et al. [12] used the finite-difference method with a strip-fins convective

No abstract

The power from lithium-ion batteries can be retired from electric vehicles (EVs) and can be used for energy storage applications when the residual capacity is up to 70% of their initial capacity. The retired batteries have characteristics of serious inconsistency. In order to solve this problem, a layered bidirectional active equalization topology is proposed in this paper. Specifically, a bridge-type equalization topology based on an inductor is adopted in the bottom layer, and the distributed equalization topological structure based on the bidirectional BUCK-BOOST circuit is adopted in the top layer. State of charge (SOC) is used as the equalization target variable, and the bottom layer equalization algorithm based on a “partition” idea and route optimization is proposed. The static equalization experiments and charge equalization experiments are performed by the 12 retired batteries selected from an electric sanitation vehicle. The results show that the proposed equalization method can reduce the SOC difference between retired batteries and can effectively improve the inconsistency of the retired battery pack with a faster equalization speed.