Electric dump trucks (EDTs) are expected to work in fast-changing conditions of torque and speed, which causes the inefficient working status of traction motors. To improve the economic performance of the dump truck, a novel integrated dual-motor transmission (IDMT) is proposed in this article. The energy consumption level of this kind of system relies on a wise energy management strategy. This article presents a dynamic power distribution strategy (DPDS) for the proposed system. By coordinating the output torque allocation of the two motors based on the efficiency map partition and optimal dynamic torque allocation ratio, the proposed strategy is more effective for real-time application compared to the previously proposed enumeration strategy. In addition, a particle swarm optimization is carried out to search for the optimal combination of the gear ratios for the selected EDT. The dynamic model of the IDMT and a detailed mathematical model of the EDT are developed to validate the performance of the proposed design and strategy. The simulation and experiment results show the energy-save and real-time ability of the developed strategy and indicate that the proposed structure can appreciably improve economic performance and enhance battery life.

Due to the different working conditions and specification requirements of mining trucks when compared to commercial passenger vehicles, better fuel efficiency of mining trucks could lead to more significant economic benefits. Therefore, investigating a hybrid transmission system becomes essential. A coaxial power-split hybrid powertrain system for mining trucks is presented in this paper. The system is characterized as comprising an engine, a generator (MG1), a motor (MC2), two sets of planetary gears, and a clutch (CL1). There are six primary operation modes for the hybrid system including the electric motor mode, the engine mode, the hybrid electric mode, the hybrid and assist mode, the regenerative mode, and the stationary charging mode. The mathematical model of the coaxial power-split hybrid system is established according to the requirements of vehicle dynamic performance and fuel economy performance in a given driving cycle. A hybrid vehicle model based on a rule-based control strategy is established to evaluate the fuel economy. Compared with the Toyota Hybrid System (THS) and the conventional mechanical vehicle system using a diesel engine, the simulation results based on an enterprise project indicate that the proposed hybrid system can enhance the vehicle’s fuel economy by 8.21% and 22.45%, respectively, during the given mining driving cycle. The simulation results can be used as a reference to study the feasibility of the proposed coaxial hybrid system whose full potential needs to be further investigated by adopting non-causal control strategies.

Unmanned mining is one of the essential fields of mining technology at present. Therefore, optimisation with known driving speed cycle for fuel economy, emissions, driveability, and more is no longer exclusive, the optimal velocity trajectory based on road information has been studied. Given that both fuel consumption and transport time influence transport costs of mining trucks, an energy management strategy (EMS) based on velocity optimisation is proposed and illustrated on a series hybrid electric mining truck in this study. The vehicle speed and SOC are adopted as state variables. Then two‐scale dynamic programming is applied to calculate optimum velocity trajectory and power distribution. Simulation results reveal that the weighting coefficients of transport time and fuel economy can be optimally distributed for the different design requirements. Compared to the results under the known driving speed cycle, the proposed EMS can enhance fuel economy by 26.59% under the guarantee of same transport time, or transport time can be reduced by 42.4% without sacrificing the fuel consumption. Therefore, the proposed velocity optimisation strategy can reduce transport costs for mining enterprises significantly.

Urban logistics holds the lifeline of global business and consumption demand. The amount of transport vehicles rises gradually but also leads to graver emission problem. Therefore, electrified vehicles are considered as better options to substitute traditional logistics vehicles. Extended range electric logistics van (ERELV) provides a solution by providing satisfactory driving range and lower production cost than battery electric logistics van (BELV). This work aims to present a thorough energy consumption and total cost of ownership (TCO) analysis for an extended range electric van to present its energy potential. Both the ERELV and BELV mathematical models are constructed and compared, and their long-term battery degradation comparison is studied for the first time. Dynamic programming (DP) is adopted in the energy management strategy for energy consumption optimization, and the global optimization result reveals the optimal energy consumption of the ERELV. Comparative results demonstrate that the ERELV has a relatively longer drive distance, slower battery aging trend, and cheaper TCO (6.6%) when comparing to the BELV. The adoption of ERELV will promisingly reduce operating cost as the alternative transportation solution for urban logistics.

Considering the energy consumption and specific performance requirements of mining trucks, a novel uninterrupted multi-speed transmission is proposed in this paper, which is composed of a power-split device, and a three-speed lay-shaft transmission with a traction motor. The power-split device is adapted to enhance the efficiency of the engine by adjusting the gear ratio continuously. The three-speed lay-shaft transmission is designed based on the efficiency map of traction motor to guarantee the drivability. The combination of the power-split device and three-speed lay-shaft transmission can realize uninterrupted gear shifting with the proposed shift strategy, which benefits from the proposed adjunct function by adequately compensating the torque hole. The detailed dynamic models of the system are built to verify the effectiveness of the proposed shift strategy. To evaluate the maximum fuel efficiency that the proposed uninterrupted multi-speed transmission could achieve, dynamic programming is implemented as the baseline. Due to the “dimension curse” of dynamic programming, a real-time control strategy is designed, which can significantly improve the computing efficiency. The simulation results demonstrate that the proposed uninterrupted multi-speed transmission with dynamic programming and real-time control strategy can improve fuel efficiency by 11.63% and 8.51% compared with conventional automated manual transmission system, respectively.