## 3 Results
### Analysis and Synthesis
#### 3.1.3 MPC EMSs  
The MPC was introduced to overcome the issue of the DP algorithm that obtains the global optimum control when all future information is known in advance (driving cycle, state of the vehicle, etc.). Such conditions are impractical for real-time applications. The MPC operates based on a receding-horizon control strategy with a predictive scheme. However, the performance of MPC is sensitive to the model quality and sensor accuracy. To minimize the mismatch and disturbances, the horizon length of the MPC has to be tuned. In [29], an MPC was proposed to solve the conflict between the energy consumption cost and the equivalent battery life cost. The proposed EMS was examined by real-world driving cycles under different preview horizons (5, 10 and 15 s). Meanwhile, global optimization algorithms like the DP as well as an RB method were compared with the predictive controller. The results indicated that the proposed MPC could significantly reduce the equivalent battery life loss cost and thus the total cost (more than 12.2% for the three preview horizons, compared to the CDCS method). A similar idea was proposed in [34], which added driving safety to the energy consumption and battery degradation objectives. An MPC was proposed to minimize the combined cost of the energy consumption cost, the equivalent cost of battery life lost and driving safety over a moving horizon. To evaluate the proposed method, it was compared to other methods, such as CDCS and DP, showing a significant advantage compared to conventional methods. The focus in [31] was on improving the vehicle speed prediction accuracy and computational efficiency of MPC. The use of a search acceleration method was proposed, specifically the A* algorithm, to reduce the calculation time while optimizing the EMS. Furthermore, the accelerated MPC was combined with an RB strategy extracted from the DP results. The proposed EMS was compared with DP and a common RB method, resulting in a fuel economy near to the DP and better than the RB. In addition, HIL tests were performed to validate its real-time performance. [PERSON] et al. [33] highlighted that the research about MPC EMSs in PHEVs was focused on three aspects: solution algorithms in the receding horizon, methods of future velocity profile acquisition and SOC reference trajectory planning methods. They developed a new velocity prediction method called synthesized velocity profile prediction (SVPP), which integrated macroscopically and microcosmically predicted velocities obtained by the participatory sensing data (PSD)-based method and the Markov chain (MC), respectively, which were synthesized by the linear regression method. The capability of the proposed scheme in terms of fuel economy was demonstrated by comparing this metric with those of DP and CDCS EMS through simulation. A different approach to velocity prediction, based on the idea of distributing the computation load using mobile edge computation and on-board vehicle control units, was presented in [30]. The resulting method was called compound velocity profile prediction (CVPP) and was applied to the EMS of a PHEV. The proposed EMS was compared to DP, other MPC methods and the CDCS strategy. Compared with other MPC-based methods, the CVPP-MPC achieved better fuel economy as a result of a more accurate velocity prediction. In [32], to reduce online computation time and microprocessor hardware resources, the solution adopted was to obtain the explicit MPC (EMPC) control laws by solving the multi-parameter quadratic programming optimization problem offline. Then, the laws were used online to realize the real-time control. A DP-based control strategy and an RB control strategy were considered benchmark strategies for the verification of the proposed EMPC-based EMS through simulation. As the prediction horizon increased, although the fuel economy of a common MPC EMS and the proposed EMPC EMS remained nearly the same, the computation time of the first increased significantly while the computation time of the proposed one was nearly unchanged.