When driving in mountainous areas, vehicles often encounter downhill conditions. To ensure safe driving, it is necessary to control the speed of vehicles. For internal combustion engine vehicles, auxiliary brake such as engine brake can be used to alleviate the thermal load caused by the continuous braking of the friction brake. For battery electric vehicles (BEVs), regenerative braking can be used as auxiliary braking to improve brake safety. And through regenerative braking, energy can be partly converted into electrical energy and stored in accumulators (such as power batteries and supercapacitors), thus extending the mileage.
However, the driver's line of sight in the mountains is limited, resulting in a certain degree of blindness in driving, so it is impossible to fully guarantee the safety and energy saving of downhill driving. Therefore, taking a pure electric light truck as an example, the system proposed in this paper first analyzes the driver's driving intention, proposes the system startup and exit strategy, and then combines the geographic information system (GIS) mountain road information, downslope speed limit and vehicle parameters, considering the motor and battery characteristics, establishes mathematical models such as the regenerative braking model and the brake temperature rise model based on vehicle dynamics and the conservation of energy, determines the appropriate braking mode(There are two braking modes)and the slope top safe speed by calculation, and reminds the driver when going uphill and downhill. The main goal is to use more regenerative braking, reduce the use or duration of the main brake, avoid overheating the main brake, improve the safety during continuous braking, and achieve smarter energy management. Finally, simulations are carried out under different conditions of vehicle speed, slope length, slope gradient and battery SOC. The results show that the system has a good energy-saving effect and can significantly improve the safety of BEVs running downhill.