# An Overview of Modelling and Energy Management Strategies for Hybrid Electric Vehicles
## 3 Research and Current Status of Energy Management Strategies for HEVs  
Control methods can usually be divided into two types. One is the bottom-level control involving the vehicle components, which generally controls each part of the vehicle's powertrain through the use of feedback control [43; 44]. The other is the top-level control, which is responsible for planning and controlling the energy flow to ensure that physical variables such as the state of charge (SOC) are maintained within a more desirable range [45]. Specifically, energy management for HEVs requires a strategy that allows the upper-level controller to determine the amount of energy delivered at each moment, satisfying driveline, powertrain, and other constraints. Energy management strategies can calculate the required driving or braking torque at each moment based on the vehicle's state, such as the battery SOC, vehicle speed, and the operating mode. Then, it will allocate this torque to power the components and to meet the vehicle's moving requirements. In fact, a proper energy distribution strategy is able to improve not only the power performance but also the fuel economy of the vehicles. It is shown in Figure 4 how the energy management system acts [46; 47; 48].  
The external control is speed control, which is the role played by the driver in a real moving vehicle and is usually replaced in a simulation model by a driver model [49]. In order to ensure that the actual vehicle speed is close to the reference working speed, the driver model controls the demanded power supplied to the vehicle by adjusting the different throttle and brake pedal openings. The internal control is the vehicle's energy management system, which allocates the demanded power to the engine and battery via a built-in strategy [50; 51].  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Configuration** & **References** & **Advantages** & **Disadvantages** \\ \hline Series hybrid & [29; 30; 31; 32; 39] & Simple structure; & High number of energy conversions; \\ electric vehicle & & Optimization is relatively simple & Not energy efficient \\ Parallel hybrid & [33; 34; 35; 36; 41] & High energy efficiency; & Complex control strategies; \\ electric vehicle & & Rational torque distribution & Large control difficulty \\ Series–parallel & & Multiple working modes; & Complicated arrangement structure; \\ hybrid electric vehicle & & High energy efficiency & High computational costs \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of the various configurations.  
Figure 4: The role of the energy management system in HEV control.  
Figure 3: Structural diagram of the hybrid construction.  
Contrary to pure electric and fuel vehicles, HEVs have various power sources and driving modes, which complicates their structural layout and increases the complexity of their control variables [52]. HEVs have demonstrated a significant improvement in vehicle fuel economy and emission reduction while still meeting power requirements and maintaining satisfactory vehicle performance and driving comfort. As the technology has advanced, existing energy management strategies are broadly categorized into three groups: rule-based energy management strategies, optimization-based energy management strategies, and learning-based energy management strategies [34; 53; 54; 55]. The main classifications and theoretical distributions are shown in Figure 5.